Kanetis 2022: Sporocadaceae from grapevine trunk diseases in Cyprus

The session

This is the session as the scientist sees it, in order. Decision cards show the answer that the script gave and where that answer comes from. Each step shows the program, its version, the input file hash and the outputs. Click a line to see more.

- Setup values:
Alignment:
- Alignment method (MAFFT) (algorithm): auto
- Trim the alignment (trim): false
Tree:
- Substitution model (model): TIM2e+I+G4
- Bootstrap type (bootstrap_type): ufboot
- Number of bootstrap replicates (replicates): 1000
- Outgroup (outgroup): Beltrania_rhombica_CBS_123.58
- Random seed (seed): 1
Ask the scientist: Largest gap fraction of a kept column (max_gap_fraction).
Fixed by the lab: Random seed (seed) = 1.
The harness fills these values into your tool calls automatically. If you give a different value, the harness logs a deviation and shows it to the scientist.
- Mode is now watch: you run the steps.

n_sequences=55
alignment_length=2375
gap_fraction=0.1524
constant_columns=1033
mean_pairwise_identity=0.9221

report={work}/infer_tree-1/run.iqtree
seed=1
bootstrap_type=ufboot
bootstrap_replicates=1000
treefile={work}/infer_tree-1/run.treefile
consensus_tree={work}/infer_tree-1/run.contree
n_sequences=55
n_sites=2375
model=TIM2e+I+G4
log_likelihood=-15895.4825
tree_length=2.1859
constant_sites=1546
site_patterns=891

((((((((((((L240:0.0000000000,L106:0.0000000000):0.0000000000,Sporocadus_rosigena_CBS_182.50:0.0000000000):0.0000010036,L105:0.0000010036)100:0.0225945249,Sporocadus_sorbi_CBS_160.25:0.0142866902)100:0.0099681337,(((L158:0.0000000000,L181:0.0000000000):0.0000000000,Sporocadus_kurdistanicus_CBS_143778:0.0000000000):0.0000010036,L164:0.0000010036)100:0.0228974432)98:0.0101560371,(((Sporocadus_glandigenus_NBRC_32677:0.0000010036,Sporocadus_lichenicola_CBS_354.90:0.0004996346)85:0.0000016711,Sporocadus_lichenicola_CPC_24528:0.0000025721)100:0.0183690192,Sporocadus_cornicola_CBS_143889:0.0157333264)100:0.0182073198)87:0.0033293794,Sporocadus_cornii_MFLUCC_140467:0.0176349188)77:0.0252172339,(((Sporocadus_rotundatus_CBS_616.83:0.0353251872,(Sporocadus_microcyclus_CBS_887.68:0.0388413239,Sporocadus_biseptatus_CBS_110324:0.0428952437)100:0.0149950389)79:0.0018540152,Sporocadus_cotini_CBS_139966:0.0434450980)97:0.0047389945,((Sporocadus_italicus_MFLUCC_141196:0.0111865557,Sporocadus_incanus_CBS_123003:0.0000010036)100:0.0265171113,Sporocadus_mali_CBS_446.70:0.0325974150)83:0.0030055076)92:0.0044195526)55:0.0039323612,Sporocadus_multiseptatus_CBS_143899:0.0457447890)34:0.0016505774,(Sporocadus_trimorphus_CBS_114203:0.0309357869,Sporocadus_rosarum_CBS_113832:0.0294613387)99:0.0154612969)99:0.0327600758,(((((Seimatosporium_parasiticum_NBRC_32682:0.0036981196,Seimatosporium_physocarpi_CBS_139968:0.0000010036)100:0.0512691444,((Seimatosporium_pistaciae_CBS_138865:0.0005144449,Seimatosporium_rosae_CBS_139823:0.0010081322)99:0.0051708238,Seimatosporium_germanicum_CBS_437.87:0.0063897401)100:0.0411146813)45:0.0056368647,Seimatosporium_soli_CBS_941.69:0.0626071872)50:0.0017780239,((Seimatosporium_vitis_Napa764:0.0000026589,((Seimatosporium_vitis-viniferae_CBS_123004:0.0000010036,P210:0.0000010036)85:0.0000020179,(Seimatosporium_vitis_MFLUCC_140051:0.0000023677,((((((L189:0.0000000000,P46:0.0000000000):0.0000000000,P56:0.0000000000):0.0000000000,P57:0.0000000000):0.0000000000,L34:0.0000000000):0.0000000000,L33:0.0000000000):0.0000010036,P60:0.0000010036)88:0.0005088045)51:0.0000014529)73:0.0015300574)100:0.0308220825,(Seimatosporium_luteosporum_CBS_142599:0.0113782173,(Seimatosporium_vitifusiforme_CBS_142600:0.0009980172,(Seimatosporium_marivanicum_CBS_143781:0.0005045496,(L112:0.0000010036,L111:0.0000010036)100:0.0009989992)100:0.0030363769)100:0.0062828263)100:0.0221077216)93:0.0080542188)74:0.0152035463,(Seimatosporium_discosioides_NBRC_104201:0.0666348475,Seimatosporium_botan_NBRC_104200:0.0429771506)99:0.0351616550)89:0.0217647923)88:0.0241731915,Beltrania_rhombica_CBS_123.58:0.5220627674,(((Allelochaeta_biseptata_CBS_131116:0.0648076439,Allelochaeta_fusispora_CBS_144172:0.0852661249)99:0.0243147389,(Sarcostroma_grevilleae_CBS_101.71:0.0426979273,(Sarcostroma_diversiseptatum_CBS_189.81:0.0297680800,Sarcostroma_restionis_CBS_118154:0.0204196866)100:0.0198777805)100:0.0437806824)100:0.0691693969,Diploceras_hypericinum_CBS_143885:0.1774432908)91:0.0162912471);

p='{work}/infer_tree-1/run.log'
for l in open(p):
    if any(k in l for k in ['WARN','identical','IQ-TREE','version','Alignment has','Log-likelihood of consensus','BEST SCORE']):
        print(l.rstrip())

IQ-TREE single-core version 3.1.4 for MacOS ARM 64-bit built Sep 10 2026
NOTE: Consider using the multicore version because your CPU has 12 cores!
WARNING: 1 sites contain only gaps or ambiguous characters.
Alignment has 55 sequences with 2375 columns, 891 distinct patterns
NOTE: L105 is identical to L240 but kept for subsequent analysis
NOTE: P210 is identical to Seimatosporium_vitis-viniferae_CBS_123004 but kept for subsequent analysis
NOTE: L164 is identical to L158 but kept for subsequent analysis
NOTE: P60 is identical to L189 but kept for subsequent analysis
NOTE: L111 is identical to L112 but kept for subsequent analysis
NOTE: 9 identical sequences (see below) will be ignored for subsequent analysis
NOTE: L106 (identical to L240) is ignored but added at the end
NOTE: Sporocadus_rosigena_CBS_182.50 (identical to L240) is ignored but added at the end
NOTE: L181 (identical to L158) is ignored but added at the end
NOTE: Sporocadus_kurdistanicus_CBS_143778 (identical to L158) is ignored but added at the end
NOTE: P46 (identical to L189) is ignored but added at the end
NOTE: P57 (identical to L189) is ignored but added at the end
NOTE: L34 (identical to L189) is ignored but added at the end
NOTE: L33 (identical to L189) is ignored but added at the end
NOTE: P56 (identical to L189) is ignored but added at the end
BEST SCORE FOUND : -15895.482
Log-likelihood of consensus tree: -15895.737
  IQ-TREE report:                {work}/infer_tree-1/run.iqtree

{"items":[{"name":"reference_sequences","expression":"55 - 16"},{"name":"L111_to_S_marivanicum_distance","expression":"0.0009989992 + 0.0000010036 + 0.0005045496"},{"name":"variable_sites_iqtree","expression":"2375 - 1546"}],"purpose":"Count the reference sequences, the variable sites, and the tree distance from L111 to its sister species."}

reference_sequences = 55 - 16 = 39
L111_to_S_marivanicum_distance = 0.0009989992 + 0.0000010036 + 0.0005045496 = 0.0015045524
variable_sites_iqtree = 2375 - 1546 = 829

from ga_api import save_table
rows=[]
def add(iso,ref,sup,note):
    for i in iso: rows.append({'isolate':i,'nearest_reference':ref,'clade_ufboot':sup,'note':note})
add(['L240','L106','L105'],'Sporocadus rosigena CBS 182.50',100,'L240 and L106 identical to reference; L105 identical to L240 in IQ-TREE check')
add(['L158','L181','L164'],'Sporocadus kurdistanicus CBS 143778',100,'L158 and L181 identical to reference; L164 identical to L158')
add(['P210'],'Seimatosporium vitis-viniferae CBS 123004',100,'identical to reference; pair support 85; clade with S. vitis strains support 100')
add(['L189','P46','P56','P57','L34','L33','P60'],'Seimatosporium vitis MFLUCC 14-0051 / S. vitis-viniferae complex',100,'7 isolates identical; subclade 88; link to S. vitis MFLUCC 51; complex clade 100')
add(['L111','L112'],'Seimatosporium marivanicum CBS 143781',100,'identical to each other; sister to S. marivanicum, support 100; not identical to it')
save_table('isolate_placement',rows)
print(len(rows))

16

- 9 numbers in the answer match no logged tool result: 95, 182.5, 143778, 123004, 143781, 14. Run the tool that measures each number, or remove the number, or say how you derived it from logged results.
Fix these problems. Then give the answer again.

The final answer

The model wrote this answer. The harness shows it to the scientist after the review.

Step results that the answer does not mention, from the record:
- n3 run_script: The script ran in {work} and wrote 0 new file(s) to {work}.
- n5 run_script: The script ran in {work} and wrote 1 new file(s) to {work}.

Settings used, from the decision record: Substitution model: TIM2e+I+G4 · Bootstrap type: ufboot · Number of bootstrap replicates: 1000 · Outgroup: Beltrania_rhombica_CBS_123.58 · Random seed: 1.

Values that are not scored

• A trap value is the result of a wrong method, for example an unpaired test on paired data. A trap value in a main step means that the run used the wrong method. A trap value in a comparison run is correct, because the record keeps the scientist's choice.
• An optional value is a second result of the same method. The run can compute it or not.
• A reference value comes from a different program version or a check run by us. We show it for comparison.

Checks

Review findings

The review recorded 10 findings. A rule finding comes from a fixed check in the harness. A referee finding comes from a second model that reads the record. The harness shows the findings to the scientist with the final answer. The record does not mark a finding as fixed. Thus a finding from an early review round can apply to a draft that the model corrected later.

Numbers in the answer

The last claim check read 48 numbers in the answer. 40 numbers match a logged result. 7 numbers have no source in the record.

Deviations

The model did not try to change a choice of the scientist.

Failed tool calls

No tool call failed.

Data integrity

Each data file has the same SHA-256 hash now as at the time of the step that read it. Where the download script (fetch.sh) gives a hash, the file also has that hash. The run did not change the data.

A SHA-256 hash is a fingerprint of the file contents. If one byte of the file changes, the hash changes. The table shows the first 12 characters.

How to repeat it

Get the data. The script downloads the files and checks their SHA-256 hashes where it lists them.

CUVETTE_DATA={data} bash bench/papers/kanetis2022-iqtree-sporocadaceae/fetch.sh

Run the same case with Cuvette. The script gives the same answers from bench/papers/kanetis2022-iqtree-sporocadaceae/bench.yaml.

cuvette bench papers --papers kanetis2022-iqtree-sporocadaceae --models claude:claude-opus-5-5

Repeat each step by hand in the program. For each step, the harness records a manual route: the menu path or the code that gives the same result. This list does not include comparison runs.

1. alignment_stats (step n1)

   Open the alignment in an alignment viewer such as AliView or Jalview and read the sequence count and the alignment length.

   • alignment file

     {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/claude-final/catalog/phylo/scripts/py.sh fasta_stats.py {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   The program has no menu route for this step. To repeat it, run the code.

2. infer_tree (step n2)

   Run: iqtree3 -s <alignment> -m <model> -B <replicates> -seed <seed> -T 1

   • -s

     {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   • -m = TIM2e+I+G4
   • -B = 1000
   • -o = Beltrania_rhombica_CBS_123.58
   • -seed = 1
   • Warning: If you keep the default MFP, you get a different result.
   • Warning: If you keep the default , you get a different result.
   • Warning: If you keep the default random, you get a different result.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/claude-final/catalog/phylo/scripts/iqtree.sh /opt/homebrew/bin/iqtree3 infer --alignment {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas --model TIM2e+I+G4 --bootstrap-type ufboot --replicates 1000 --outgroup Beltrania_rhombica_CBS_123.58 --seed 1

   The manual route gives the same numbers. An automatic test in Cuvette checks this.

3. run_script (step n3)

   Run the Python code in {work}/script-1/script.py

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The program has no menu route for this step. To repeat it, run the code.

4. calculate (step n4)

   Run the tool "calculate" with these settings: {"items":[{"name":"reference_sequences","expression":"55 - 16"},{"name":"L111_to_S_marivanicum_distance","expression":"0.0009989992 + 0.0000010036 + 0.0005045496"},{"name":"variable_sites_iqtree","expression":"2375 - 1546"}]}.
   - Code only: this step has no route in the program menus. Run it with the script or flow export.

   The harness recorded no manual route for this step.

5. run_script (step n5)

   Run the Python code in {work}/script-2/script.py

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The program has no menu route for this step. To repeat it, run the code.

Figure

Run facts

The session

This is the session as the scientist sees it, in order. Decision cards show the answer that the script gave and where that answer comes from. Each step shows the program, its version, the input file hash and the outputs. Click a line to see more.

- Setup values:
Alignment:
- Alignment method (MAFFT) (algorithm): auto
- Trim the alignment (trim): false
Tree:
- Substitution model (model): TIM2e+I+G4
- Bootstrap type (bootstrap_type): ufboot
- Number of bootstrap replicates (replicates): 1000
- Outgroup (outgroup): Beltrania_rhombica_CBS_123.58
- Random seed (seed): 1
Ask the scientist: Largest gap fraction of a kept column (max_gap_fraction).
Fixed by the lab: Random seed (seed) = 1.
The harness fills these values into your tool calls automatically. If you give a different value, the harness logs a deviation and shows it to the scientist.
- Mode is now watch: you run the steps.

n_sequences=55
alignment_length=2375
gap_fraction=0.1524
constant_columns=1033
mean_pairwise_identity=0.9221

report={work}/infer_tree-1/run.iqtree
seed=1
bootstrap_type=ufboot
bootstrap_replicates=1000
treefile={work}/infer_tree-1/run.treefile
consensus_tree={work}/infer_tree-1/run.contree
n_sequences=55
n_sites=2375
model=TIM2e+I+G4
log_likelihood=-15895.4825
tree_length=2.1859
constant_sites=1546
site_patterns=891

import re
p="{work}/infer_tree-1/run.treefile"
s=open(p).read().strip()
class N: 
    def __init__(s): s.ch=[];s.name=None;s.sup=None;s.par=None
pos=0
def parse():
    global pos
    n=N()
    if s[pos]=='(':
        pos+=1
        while True:
            c=parse();c.par=n;n.ch.append(c)
            if s[pos]==',': pos+=1;continue
            if s[pos]==')': pos+=1;break
        m=re.match(r'[^:,();]*',s[pos:]);lab=m.group(0);pos+=len(lab)
        n.sup=lab or None
    else:
        m=re.match(r'[^:,();]*',s[pos:]);n.name=m.group(0);pos+=len(n.name)
    if pos<len(s) and s[pos]==':':
        m=re.match(r':[^,();]*',s[pos:]);pos+=len(m.group(0))
    return n
root=parse()
def leaves(n):
    return [n.name] if n.name else [l for c in n.ch for l in leaves(c)]
allv=leaves(root);print(len(allv))
print(sorted(allv))
print(root.sup,len(root.ch))

55
['Allelochaeta_biseptata_CBS_131116', 'Allelochaeta_fusispora_CBS_144172', 'Beltrania_rhombica_CBS_123.58', 'Diploceras_hypericinum_CBS_143885', 'L105', 'L106', 'L111', 'L112', 'L158', 'L164', 'L181', 'L189', 'L240', 'L33', 'L34', 'P210', 'P46', 'P56', 'P57', 'P60', 'Sarcostroma_diversiseptatum_CBS_189.81', 'Sarcostroma_grevilleae_CBS_101.71', 'Sarcostroma_restionis_CBS_118154', 'Seimatosporium_botan_NBRC_104200', 'Seimatosporium_discosioides_NBRC_104201', 'Seimatosporium_germanicum_CBS_437.87', 'Seimatosporium_luteosporum_CBS_142599', 'Seimatosporium_marivanicum_CBS_143781', 'Seimatosporium_parasiticum_NBRC_32682', 'Seimatosporium_physocarpi_CBS_139968', 'Seimatosporium_pistaciae_CBS_138865', 'Seimatosporium_rosae_CBS_139823', 'Seimatosporium_soli_CBS_941.69', 'Seimatosporium_vitifusiforme_CBS_142600', 'Seimatosporium_vitis-viniferae_CBS_123004', 'Seimatosporium_vitis_MFLUCC_140051', 'Seimatosporium_vitis_Napa764', 'Sporocadus_biseptatus_CBS_110324', 'Sporocadus_cornicola_CBS_143889', 'Sporocadus_cornii_MFLUCC_140467', 'Sporocadus_cotini_CBS_139966', 'Sporocadus_glandigenus_NBRC_32677', 'Sporocadus_incanus_CBS_123003', 'Sporocadus_italicus_MFLUCC_141196', 'Sporocadus_kurdistanicus_CBS_143778', 'Sporocadus_lichenicola_CBS_354.90', 'Sporocadus_lichenicola_CPC_24528', 'Sporocadus_mali_CBS_446.70', 'Sporocadus_microcyclus_CBS_887.68', 'Sporocadus_multiseptatus_CBS_143899', 'Sporocadus_rosarum_CBS_113832', 'Sporocadus_rosigena_CBS_182.50', 'Sporocadus_rotundatus_CBS_616.83', 'Sporocadus_sorbi_CBS_160.25', 'Sporocadus_trimorphus_CBS_114203']
None 3

import re
p="{work}/infer_tree-1/run.treefile"
s=open(p).read().strip()
class N: 
    def __init__(s): s.ch=[];s.name=None;s.sup=None;s.par=None
pos=0
def parse():
    global pos
    n=N()
    if s[pos]=='(':
        pos+=1
        while True:
            c=parse();c.par=n;n.ch.append(c)
            if s[pos]==',': pos+=1;continue
            if s[pos]==')': pos+=1;break
        m=re.match(r'[^:,();]*',s[pos:]);lab=m.group(0);pos+=len(lab)
        n.sup=lab or None
    else:
        m=re.match(r'[^:,();]*',s[pos:]);n.name=m.group(0);pos+=len(n.name)
    if pos<len(s) and s[pos]==':':
        m=re.match(r':[^,();]*',s[pos:]);pos+=len(m.group(0))
    return n
root=parse()
def show(n,d=0):
    if n.name: print("  "*d+n.name);return
    print("  "*d+"+ sup=%s n=%d"%(n.sup,len(L(n))))
    for c in n.ch: show(c,d+1)
def L(n): return [n.name] if n.name else [l for c in n.ch for l in L(c)]
show(root)

+ sup=None n=55
  + sup=88 n=48
    + sup=99 n=24
      + sup=34 n=22
        + sup=55 n=21
          + sup=77 n=14
            + sup=87 n=13
              + sup=98 n=9
                + sup=100 n=5
                  + sup=100 n=4
                    + sup=None n=3
                      + sup=None n=2
                        L240
                        L106
                      Sporocadus_rosigena_CBS_182.50
                    L105
                  Sporocadus_sorbi_CBS_160.25
                + sup=100 n=4
                  + sup=None n=3
                    + sup=None n=2
                      L158
                      L181
                    Sporocadus_kurdistanicus_CBS_143778
                  L164
              + sup=100 n=4
                + sup=100 n=3
                  + sup=85 n=2
                    Sporocadus_glandigenus_NBRC_32677
                    Sporocadus_lichenicola_CBS_354.90
                  Sporocadus_lichenicola_CPC_24528
                Sporocadus_cornicola_CBS_143889
            Sporocadus_cornii_MFLUCC_140467
          + sup=92 n=7
            + sup=97 n=4
              + sup=79 n=3
                Sporocadus_rotundatus_CBS_616.83
                + sup=100 n=2
                  Sporocadus_microcyclus_CBS_887.68
                  Sporocadus_biseptatus_CBS_110324
              Sporocadus_cotini_CBS_139966
            + sup=83 n=3
              + sup=100 n=2
                Sporocadus_italicus_MFLUCC_141196
                Sporocadus_incanus_CBS_123003
              Sporocadus_mali_CBS_446.70
        Sporocadus_multiseptatus_CBS_143899
      + sup=99 n=2
        Sporocadus_trimorphus_CBS_114203
        Sporocadus_rosarum_CBS_113832
    + sup=89 n=24
      + sup=74 n=22
        + sup=50 n=6
          + sup=45 n=5
            + sup=100 n=2
              Seimatosporium_parasiticum_NBRC_32682
              Seimatosporium_physocarpi_CBS_139968
            + sup=100 n=3
              + sup=99 n=2
                Seimatosporium_pistaciae_CBS_138865
                Seimatosporium_rosae_CBS_139823
              Seimatosporium_germanicum_CBS_437.87
          Seimatosporium_soli_CBS_941.69
        + sup=93 n=16
          + sup=100 n=11
            Seimatosporium_vitis_Napa764
            + sup=73 n=10
              + sup=85 n=2
                Seimatosporium_vitis-viniferae_CBS_123004
                P210
              + sup=51 n=8
                Seimatosporium_vitis_MFLUCC_140051
                + sup=88 n=7
                  + sup=None n=6
                    + sup=None n=5
                      + sup=None n=4
                        + sup=None n=3
                          + sup=None n=2
                            L189
                            P46
                          P56
                        P57
                      L34
                    L33
                  P60
          + sup=100 n=5
            Seimatosporium_luteosporum_CBS_142599
            + sup=100 n=4
              Seimatosporium_vitifusiforme_CBS_14
... (653 more characters in the session record)

- The answer names standard for "Bootstrap type", but the decision record says ufboot. Report the value that was used.
- 10 numbers in the answer match no logged tool result: 17, 95, 182.5, 160.25, 143778, 143781, 123004, 140051. Run the tool that measures each number, or remove the number, or say how you derived it from logged results.
- The answer says there are 17 isolates. The isolate names in the log are 16: 11 L isolates and 5 P isolates. The table also lists 16.
- The answer says the 98-support clade of 9 taxa also holds the S. glandigenus / S. lichenicola / S. cornicola group. The logged tree puts that group in a separate sister clade inside the larger 87-support clade of 13 taxa.
Fix these problems. Then give the answer again.

{"items":[{"name":"isolates","expression":"11 + 5"}],"purpose":"Count the isolates: 11 L isolates and 5 P isolates from the tree tip names."}

isolates = 11 + 5 = 16

The final answer

The model wrote this answer. The harness shows it to the scientist after the review.

Step results that the answer does not mention, from the record:
- n3 run_script: The script ran in {work} and wrote 0 new file(s) to {work}.
- n4 run_script: The script ran in {work} and wrote 0 new file(s) to {work}.

Settings used, from the decision record: Substitution model: TIM2e+I+G4 · Bootstrap type: ufboot · Number of bootstrap replicates: 1000 · Outgroup: Beltrania_rhombica_CBS_123.58 · Random seed: 1.

Values that are not scored

• A trap value is the result of a wrong method, for example an unpaired test on paired data. A trap value in a main step means that the run used the wrong method. A trap value in a comparison run is correct, because the record keeps the scientist's choice.
• An optional value is a second result of the same method. The run can compute it or not.
• A reference value comes from a different program version or a check run by us. We show it for comparison.

Checks

Review findings

The review recorded 9 findings. A rule finding comes from a fixed check in the harness. A referee finding comes from a second model that reads the record. The harness shows the findings to the scientist with the final answer. The record does not mark a finding as fixed. Thus a finding from an early review round can apply to a draft that the model corrected later.

Numbers in the answer

The last claim check read 31 numbers in the answer. 27 numbers match a logged result. 4 numbers have no source in the record.

Deviations

The model did not try to change a choice of the scientist.

Failed tool calls

No tool call failed.

Data integrity

Each data file has the same SHA-256 hash now as at the time of the step that read it. Where the download script (fetch.sh) gives a hash, the file also has that hash. The run did not change the data.

A SHA-256 hash is a fingerprint of the file contents. If one byte of the file changes, the hash changes. The table shows the first 12 characters.

How to repeat it

Get the data. The script downloads the files and checks their SHA-256 hashes where it lists them.

CUVETTE_DATA={data} bash bench/papers/kanetis2022-iqtree-sporocadaceae/fetch.sh

Run the same case with Cuvette. The script gives the same answers from bench/papers/kanetis2022-iqtree-sporocadaceae/bench.yaml.

cuvette bench papers --papers kanetis2022-iqtree-sporocadaceae --models claude:claude-sonnet-5-5

Repeat each step by hand in the program. For each step, the harness records a manual route: the menu path or the code that gives the same result. This list does not include comparison runs.

1. alignment_stats (step n1)

   Open the alignment in an alignment viewer such as AliView or Jalview and read the sequence count and the alignment length.

   • alignment file

     {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/claude-final/catalog/phylo/scripts/py.sh fasta_stats.py {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   The program has no menu route for this step. To repeat it, run the code.

2. infer_tree (step n2)

   Run: iqtree3 -s <alignment> -m <model> -B <replicates> -seed <seed> -T 1

   • -s

     {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   • -m = TIM2e+I+G4
   • -B = 1000
   • -o = Beltrania_rhombica_CBS_123.58
   • -seed = 1
   • Warning: If you keep the default MFP, you get a different result.
   • Warning: If you keep the default , you get a different result.
   • Warning: If you keep the default random, you get a different result.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/claude-final/catalog/phylo/scripts/iqtree.sh /opt/homebrew/bin/iqtree3 infer --alignment {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas --model TIM2e+I+G4 --bootstrap-type ufboot --replicates 1000 --outgroup Beltrania_rhombica_CBS_123.58 --seed 1

   The manual route gives the same numbers. An automatic test in Cuvette checks this.

3. run_script (step n3)

   Run the Python code in {work}/script-1/script.py

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The program has no menu route for this step. To repeat it, run the code.

4. run_script (step n4)

   Run the Python code in {work}/script-2/script.py

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The program has no menu route for this step. To repeat it, run the code.

5. calculate (step n5)

   Run the tool "calculate" with these settings: {"items":[{"name":"isolates","expression":"11 + 5"}]}.
   - Code only: this step has no route in the program menus. Run it with the script or flow export.

   The harness recorded no manual route for this step.

Figure

Run facts

The session

This is the session as the scientist sees it, in order. Decision cards show the answer that the script gave and where that answer comes from. Each step shows the program, its version, the input file hash and the outputs. Click a line to see more.

- Setup values:
Alignment:
- Alignment method (MAFFT) (algorithm): auto
- Trim the alignment (trim): false
Tree:
- Substitution model (model): TIM2e+I+G4
- Bootstrap type (bootstrap_type): ufboot
- Number of bootstrap replicates (replicates): 1000
- Outgroup (outgroup): Beltrania_rhombica_CBS_123.58
- Random seed (seed): 1
Ask the scientist: Largest gap fraction of a kept column (max_gap_fraction).
Fixed by the lab: Random seed (seed) = 1.
The harness fills these values into your tool calls automatically. If you give a different value, the harness logs a deviation and shows it to the scientist.
- Mode is now watch: you run the steps.

n_sequences=55
alignment_length=2375
gap_fraction=0.1524
constant_columns=1033
mean_pairwise_identity=0.9221

report={work}/infer_tree-1/run.iqtree
seed=1
bootstrap_type=ufboot
bootstrap_replicates=1000
treefile={work}/infer_tree-1/run.treefile
consensus_tree={work}/infer_tree-1/run.contree
n_sequences=55
n_sites=2375
model=TIM2e+I+G4
log_likelihood=-15895.4825
tree_length=2.1859
constant_sites=1546
site_patterns=891

(((((((((((L240:0.0000000000,Sporocadus_rosigena_CBS_182.50:0.0000000000):0.0000000000,L106:0.0000000000):0.0000026418,L105:0.0000026418)100:0.0225689016,Sporocadus_sorbi_CBS_160.25:0.0142675577)100:0.0099549175,(((L158:0.0000000000,Sporocadus_kurdistanicus_CBS_143778:0.0000000000):0.0000000000,L181:0.0000000000):0.0000026418,L164:0.0000026418)100:0.0228241899)98:0.0101713495,(((Sporocadus_glandigenus_NBRC_32677:0.0000026418,Sporocadus_lichenicola_CBS_354.90:0.0004212888)85:0.0000787313,Sporocadus_lichenicola_CPC_24528:0.0000026418)100:0.0183406927,Sporocadus_cornicola_CBS_143889:0.0157120355)100:0.0182016918)87:0.0050771713,Sporocadus_cornii_MFLUCC_140467:0.0171256315)77:0.0232118317,(((Sporocadus_rotundatus_CBS_616.83:0.0352538025,(Sporocadus_microcyclus_CBS_887.68:0.0387716548,Sporocadus_biseptatus_CBS_110324:0.0428311787)100:0.0150223497)79:0.0018409266,Sporocadus_cotini_CBS_139966:0.0433573859)97:0.0045728264,((Sporocadus_italicus_MFLUCC_141196:0.0111579646,Sporocadus_incanus_CBS_123003:0.0000029116)100:0.0264765781,Sporocadus_mali_CBS_446.70:0.0324734195)83:0.0032021753)92:0.0046178546)55:0.0032099558,(Sporocadus_multiseptatus_CBS_143899:0.0446830712,(Sporocadus_trimorphus_CBS_114203:0.0309232887,Sporocadus_rosarum_CBS_113832:0.0291773101)99:0.0157207936)44:0.0024350255)99:0.0334597374,(((((Seimatosporium_parasiticum_NBRC_32682:0.0036921425,Seimatosporium_physocarpi_CBS_139968:0.0000020482)100:0.0511119634,((Seimatosporium_pistaciae_CBS_138865:0.0005128463,Seimatosporium_rosae_CBS_139823:0.0010068973)99:0.0051507598,Seimatosporium_germanicum_CBS_437.87:0.0064026151)100:0.0411948964)45:0.0054049002,Seimatosporium_soli_CBS_941.69:0.0630413226)50:0.0018605221,((Seimatosporium_vitis_Napa764:0.0000017953,((Seimatosporium_vitis-viniferae_CBS_123004:0.0000026418,P210:0.0000026418)85:0.0000026418,(Seimatosporium_vitis_MFLUCC_140051:0.0000026418,((((((L189:0.0000000000,P46:0.0000000000):0.0000000000,P56:0.0000000000):0.0000000000,L33:0.0000000000):0.0000000000,P57:0.0000000000):0.0000000000,L34:0.0000000000):0.0000026418,P60:0.0000026418)88:0.0000873676)51:0.0004212888)73:0.0015291862)100:0.0309798674,(Seimatosporium_luteosporum_CBS_142599:0.0113685749,(Seimatosporium_vitifusiforme_CBS_142600:0.0009966875,(Seimatosporium_marivanicum_CBS_143781:0.0005029845,(L112:0.0000026418,L111:0.0000026418)100:0.0009975947)100:0.0030345734)100:0.0062809077)100:0.0219225198)93:0.0081156220)74:0.0152530217,(Seimatosporium_discosioides_NBRC_104201:0.0663878881,Seimatosporium_botan_NBRC_104200:0.0431020646)99:0.0351046364)89:0.0219327127)88:0.0241765933,Beltrania_rhombica_CBS_123.58:0.5208975530,(((Allelochaeta_biseptata_CBS_131116:0.0647901855,Allelochaeta_fusispora_CBS_144172:0.0851013596)99:0.0243584562,(Sarcostroma_grevilleae_CBS_101.71:0.0426769354,(Sarcostroma_diversiseptatum_CBS_189.81:0.0297433663,Sarcostroma_restionis_CBS_118154:0.0203963284)100:0.0198429109)100:0.0436388076)100:0.0689898040,Diploceras_hypericinum_CBS_143885:0.1771501644)91:0.0161387060);

import re, csv
path = "{work}/infer_tree-1/run.contree"
s = open(path).read().strip()
tokens = re.findall(r'\(|\)|,|[^(),:;]+(?::[0-9.eE+-]+)?|;', s)
# simple recursive parser
pos = 0
def parse():
    global pos
    node = {'children': [], 'name': None, 'support': None}
    if tokens[pos] == '(':
        pos += 1
        while True:
            child = parse()
            node['children'].append(child)
            if tokens[pos] == ',':
                pos += 1
                continue
            elif tokens[pos] == ')':
                pos += 1
                break
        # internal label (support) possibly before ':'
        if pos < len(tokens) and tokens[pos] not in '(),;':
            lab = tokens[pos].split(':')[0]
            node['support'] = lab if lab else None
            pos += 1
    else:
        tok = tokens[pos]; pos += 1
        node['name'] = tok.split(':')[0]
    return node
root = parse()
def leaves(n):
    if not n['children']:
        return [n['name']]
    out = []
    for c in n['children']:
        out += leaves(c)
    return out
parent_map = {}
def walk(n, parent):
    if parent is not None:
        parent_map[id(n)] = parent
    for c in n['children']:
        walk(c, n)
walk(root, None)
allnodes = []
def collect(n):
    allnodes.append(n)
    for c in n['children']:
        collect(c)
collect(root)
isolates = [x for x in leaves(root) if x and x[0] in 'LP' and x[1:].isdigit()]
rows = []
for iso in isolates:
    # walk up from the leaf until the clade has a reference
    node = [n for n in allnodes if n['name'] == iso][0]
    cur = node
    while True:
        p = parent_map.get(id(cur))
        if p is None:
            break
        refs = [x for x in leaves(p) if not (x[0] in 'LP' and x[1:].isdigit())]
        if refs:
            break
        cur = p
    p = parent_map.get(id(cur))
    # the clade found is the parent node; list references inside it
    clade = leaves(p) if p else leaves(cur)
    refs = [x for x in clade if not (x[0] in 'LP' and x[1:].isdigit())]
    isos = [x for x in clade if (x[0] in 'LP' and x[1:].isdigit())]
    sup = p['support'] if p else None
    rows.append({'isolate': iso, 'smallest_clade_with_reference_support': sup,
                 'references_in_clade': '; '.join(refs), 'isolates_in_clade': '; '.join(isos), 'clade_size': len(clade)})
for r in rows:
    print(r['isolate'], '| support', r['smallest_clade_with_reference_support'], '| refs:', r['references_in_clade'], '| isolates:', r['isolates_in_clade'], '| size', r['clade_size'])
with open('isolate_groupings.csv', 'w', newline='') as f:
    w = csv.DictWriter(f, fieldnames=list(rows[0].keys()))
    w.writeheader(); w.writerows(rows)
print('n isolates', len(isolates))

L240 | support 0.0000000000 | refs: Sporocadus_rosigena_CBS_182.50 | isolates: L240 | size 2
L106 | support 0.0000026418 | refs: Sporocadus_rosigena_CBS_182.50 | isolates: L240; L106 | size 3
L105 | support 100 | refs: Sporocadus_rosigena_CBS_182.50 | isolates: L240; L106; L105 | size 4
L158 | support 0.0000000000 | refs: Sporocadus_kurdistanicus_CBS_143778 | isolates: L158 | size 2
L181 | support 0.0000026418 | refs: Sporocadus_kurdistanicus_CBS_143778 | isolates: L158; L181 | size 3
L164 | support 100 | refs: Sporocadus_kurdistanicus_CBS_143778 | isolates: L158; L181; L164 | size 4
P210 | support 85 | refs: Seimatosporium_vitis-viniferae_CBS_123004 | isolates: P210 | size 2
L189 | support 51 | refs: Seimatosporium_vitis_MFLUCC_140051 | isolates: L189; P46; P56; L33; P57; L34; P60 | size 8
P46 | support 51 | refs: Seimatosporium_vitis_MFLUCC_140051 | isolates: L189; P46; P56; L33; P57; L34; P60 | size 8
P56 | support 51 | refs: Seimatosporium_vitis_MFLUCC_140051 | isolates: L189; P46; P56; L33; P57; L34; P60 | size 8
L33 | support 51 | refs: Seimatosporium_vitis_MFLUCC_140051 | isolates: L189; P46; P56; L33; P57; L34; P60 | size 8
P57 | support 51 | refs: Seimatosporium_vitis_MFLUCC_140051 | isolates: L189; P46; P56; L33; P57; L34; P60 | size 8
L34 | support 51 | refs: Seimatosporium_vitis_MFLUCC_140051 | isolates: L189; P46; P56; L33; P57; L34; P60 | size 8
P60 | support 51 | refs: Seimatosporium_vitis_MFLUCC_140051 | isolates: L189; P46; P56; L33; P57; L34; P60 | size 8
L112 | support 100 | refs: Seimatosporium_marivanicum_CBS_143781 | isolates: L112; L111 | size 3
L111 | support 100 | refs: Seimatosporium_marivanicum_CBS_143781 | isolates: L112; L111 | size 3
n isolates 16

{"items":[{"name":"reference_sequences","expression":"55 - 16"}],"purpose":"Count the reference sequences by subtracting the 16 isolates from the 55 sequences."}

reference_sequences = 55 - 16 = 39

- 8 numbers in the answer match no logged tool result: 182.5, 160.25, 143778, 143781, 123004, 140051, 95. Run the tool that measures each number, or remove the number, or say how you derived it from logged results.
- The final answer says all 16 isolates sit in the Sporocadaceae clade. The logged output never checks Sporocadaceae membership. It only lists the smallest clade with a reference species for each isolate.
- The answer gives support 88 for the seven-isolate clade. The logged output gives support 51 for that group. The value 88 has no logged source.
- The answer says the L240, L106 and L105 group is sister to S. sorbi CBS 160.25 with support 100. The logged output never mentions S. sorbi, and it does not report sister relations. The sister claim must be removed or checked.
- The answer lists L111 and L112 grouping with S. marivanicum CBS 143781 with support 100. These isolates and this reference do not appear in the visible output. The printed output ends with an ellipsis, so this result must be checked before it is reported.
- The answer says some nodes in the L240 and L106 group have no support value printed. The log shows support values of 0.0000000000 and 0.0000026418 for those nodes. These values mean very weak support, and the answer does not report them as weak.
Fix these problems. Then give the answer again.

import re, csv
path = "{work}/infer_tree-1/run.contree"
s = open(path).read().strip().rstrip(';')
class Nd:
    def __init__(self):
        self.children = []; self.name = None; self.label = None; self.length = None; self.parent = None
i = 0
def parse_node():
    global i
    n = Nd()
    if s[i] == '(':
        i += 1
        while True:
            c = parse_node(); c.parent = n; n.children.append(c)
            if s[i] == ',':
                i += 1; continue
            if s[i] == ')':
                i += 1; break
            raise ValueError('bad char at %d' % i)
    else:
        j = i
        while s[i] not in ':,);': i += 1
        n.name = s[j:i]
    j = i
    while i < len(s) and s[i] not in ':,);': i += 1
    if i > j: n.label = s[j:i]
    if i < len(s) and s[i] == ':':
        i += 1; j = i
        while i < len(s) and s[i] not in ',);': i += 1
        n.length = float(s[j:i])
    return n
root = parse_node()
def leaves(n):
    if not n.children: return [n.name]
    out = []
    for c in n.children: out += leaves(c)
    return out
def allnodes(n):
    out = [n]
    for c in n.children: out += allnodes(c)
    return out
nodes = allnodes(root)
leafnodes = [n for n in nodes if not n.children]
names = [n.name for n in leafnodes]
iso_re = re.compile(r'^[LP]\d+$')
isolates = [x for x in names if iso_re.match(x)]
refs_all = [x for x in names if not iso_re.match(x)]
print('leaves:', len(names), 'isolates:', len(isolates), 'references:', len(refs_all))
print('Name check:')
for nm in ['Sporocadus_sorbi_CBS_160.25','Sporocadus_rosigena_CBS_182.50','Sporocadus_kurdistanicus_CBS_143778','Seimatosporium_marivanicum_CBS_143781','Seimatosporium_vitis-viniferae_CBS_123004','Seimatosporium_vitis_MFLUCC_140051','Seimatosporium_vitis_Napa764','Beltrania_rhombica_CBS_123.58']:
    print('  ', nm, 'present' if nm in names else 'ABSENT')
def describe(n):
    return {'support_label': n.label if n.label else 'none in tree file', 'members': sorted(leaves(n))}
rows = []
for iso in sorted(isolates):
    leaf = [x for x in leafnodes if x.name == iso][0]
    anc = leaf.parent
    while anc is not None and not [x for x in leaves(anc) if not iso_re.match(x)]:
        anc = anc.parent
    N = anc
    sis = None; sis_label = None
    if N is not None and N.parent is not None:
        others = [c for c in N.parent.children if c is not N]
        sis = sorted(sum([leaves(o) for o in others], []))
        sis_label = N.parent.label
    d = describe(N)
    rows.append({'isolate': iso, 'group_support': d['support_label'],
                 'group_members': '; '.join(d['members']),
                 'parent_support_of_group': sis_label if sis_label else 'none in tree file',
                 'sister_of_group': '; '.join(sis) if sis else ''})
    print(iso, '| group support:', d['support_label'], '| group:', d['members'], '| parent support:', sis_label, '| sister:', sis)
# the seven-isolate clade and the clade with MFLUCC_140051
seven = {'L189','P46','P56','L33','P57','L34','P
... (419 more characters in the session record)

leaves: 55 isolates: 16 references: 39
Name check:
   Sporocadus_sorbi_CBS_160.25 present
   Sporocadus_rosigena_CBS_182.50 present
   Sporocadus_kurdistanicus_CBS_143778 present
   Seimatosporium_marivanicum_CBS_143781 present
   Seimatosporium_vitis-viniferae_CBS_123004 present
   Seimatosporium_vitis_MFLUCC_140051 present
   Seimatosporium_vitis_Napa764 present
   Beltrania_rhombica_CBS_123.58 present
L105 | group support: 100 | group: ['L105', 'L106', 'L240', 'Sporocadus_rosigena_CBS_182.50'] | parent support: 100 | sister: ['Sporocadus_sorbi_CBS_160.25']
L106 | group support: none in tree file | group: ['L106', 'L240', 'Sporocadus_rosigena_CBS_182.50'] | parent support: 100 | sister: ['L105']
L111 | group support: 100 | group: ['L111', 'L112', 'Seimatosporium_marivanicum_CBS_143781'] | parent support: 100 | sister: ['Seimatosporium_vitifusiforme_CBS_142600']
L112 | group support: 100 | group: ['L111', 'L112', 'Seimatosporium_marivanicum_CBS_143781'] | parent support: 100 | sister: ['Seimatosporium_vitifusiforme_CBS_142600']
L158 | group support: none in tree file | group: ['L158', 'Sporocadus_kurdistanicus_CBS_143778'] | parent support: None | sister: ['L181']
L164 | group support: 100 | group: ['L158', 'L164', 'L181', 'Sporocadus_kurdistanicus_CBS_143778'] | parent support: 98 | sister: ['L105', 'L106', 'L240', 'Sporocadus_rosigena_CBS_182.50', 'Sporocadus_sorbi_CBS_160.25']
L181 | group support: none in tree file | group: ['L158', 'L181', 'Sporocadus_kurdistanicus_CBS_143778'] | parent support: 100 | sister: ['L164']
L189 | group support: 51 | group: ['L189', 'L33', 'L34', 'P46', 'P56', 'P57', 'P60', 'Seimatosporium_vitis_MFLUCC_140051'] | parent support: 73 | sister: ['P210', 'Seimatosporium_vitis-viniferae_CBS_123004']
L240 | group support: none in tree file | group: ['L240', 'Sporocadus_rosigena_CBS_182.50'] | parent support: None | sister: ['L106']
L33 | group support: 51 | group: ['L189', 'L33', 'L34', 'P46', 'P56', 'P57', 'P60', 'Seimatosporium_vitis_MFLUCC_140051'] | parent support: 73 | sister: ['P210', 'Seimatosporium_vitis-viniferae_CBS_123004']
L34 | group support: 51 | group: ['L189', 'L33', 'L34', 'P46', 'P56', 'P57', 'P60', 'Seimatosporium_vitis_MFLUCC_140051'] | parent support: 73 | sister: ['P210', 'Seimatosporium_vitis-viniferae_CBS_123004']
P210 | group support: 85 | group: ['P210', 'Seimatosporium_vitis-viniferae_CBS_123004'] | parent support: 73 | sister: ['L189', 'L33', 'L34', 'P46', 'P56', 'P57', 'P60', 'Seimatosporium_vitis_MFLUCC_140051']
P46 | group support: 51 | group: ['L189', 'L33', 'L34', 'P46', 'P56', 'P57', 'P60', 'Seimatosporium_vitis_MFLUCC_140051'] | parent support: 73 | sister: ['P210', 'Seimatosporium_vitis-viniferae_CBS_123004']
P56 | group support: 51 | group: ['L189', 'L33', 'L34', 'P46', 'P56', 'P57', 'P60', 'Seimatosporium_vitis_MFLUCC_140051'] | parent support: 73 | sister: ['P210', 'Seimatosporium_vitis-viniferae_CBS_123004']
P57 | group support: 51 | group: ['L189', 'L33', 'L34', 'P46', 'P56', 'P
... (565 more characters in the session record)

The final answer

The model wrote this answer. The harness shows it to the scientist after the review.

Step results that the answer does not mention, from the record:
- n3 run_script: The script ran in {work} and wrote 1 new file(s) to {work}.
- n5 run_script: The script ran in {work} and wrote 1 new file(s) to {work}.

Settings used, from the decision record: Substitution model: TIM2e+I+G4 · Bootstrap type: ufboot · Number of bootstrap replicates: 1000 · Outgroup: Beltrania_rhombica_CBS_123.58 · Random seed: 1.

Values that are not scored

• A trap value is the result of a wrong method, for example an unpaired test on paired data. A trap value in a main step means that the run used the wrong method. A trap value in a comparison run is correct, because the record keeps the scientist's choice.
• An optional value is a second result of the same method. The run can compute it or not.
• A reference value comes from a different program version or a check run by us. We show it for comparison.

Checks

Review findings

The review recorded 10 findings. A rule finding comes from a fixed check in the harness. A referee finding comes from a second model that reads the record. The harness shows the findings to the scientist with the final answer. The record does not mark a finding as fixed. Thus a finding from an early review round can apply to a draft that the model corrected later.

Numbers in the answer

The last claim check read 37 numbers in the answer. 26 numbers match a logged result. 11 numbers have no source in the record.

Deviations

The model did not try to change a choice of the scientist.

Failed tool calls

No tool call failed.

Data integrity

Each data file has the same SHA-256 hash now as at the time of the step that read it. Where the download script (fetch.sh) gives a hash, the file also has that hash. The run did not change the data.

A SHA-256 hash is a fingerprint of the file contents. If one byte of the file changes, the hash changes. The table shows the first 12 characters.

How to repeat it

Get the data. The script downloads the files and checks their SHA-256 hashes where it lists them.

CUVETTE_DATA={data} bash bench/papers/kanetis2022-iqtree-sporocadaceae/fetch.sh

Run the same case with Cuvette. The script gives the same answers from bench/papers/kanetis2022-iqtree-sporocadaceae/bench.yaml.

cuvette bench papers --papers kanetis2022-iqtree-sporocadaceae --models claude:claude-haiku-5-5

Repeat each step by hand in the program. For each step, the harness records a manual route: the menu path or the code that gives the same result. This list does not include comparison runs.

1. alignment_stats (step n1)

   Open the alignment in an alignment viewer such as AliView or Jalview and read the sequence count and the alignment length.

   • alignment file

     {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/claude-final/catalog/phylo/scripts/py.sh fasta_stats.py {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   The program has no menu route for this step. To repeat it, run the code.

2. infer_tree (step n2)

   Run: iqtree3 -s <alignment> -m <model> -B <replicates> -seed <seed> -T 1

   • -s

     {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   • -m = TIM2e+I+G4
   • -B = 1000
   • -o = Beltrania_rhombica_CBS_123.58
   • -seed = 1
   • Warning: If you keep the default MFP, you get a different result.
   • Warning: If you keep the default , you get a different result.
   • Warning: If you keep the default random, you get a different result.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/claude-final/catalog/phylo/scripts/iqtree.sh /opt/homebrew/bin/iqtree3 infer --alignment {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas --model TIM2e+I+G4 --bootstrap-type ufboot --replicates 1000 --outgroup Beltrania_rhombica_CBS_123.58 --seed 1

   The manual route gives the same numbers. An automatic test in Cuvette checks this.

3. run_script (step n3)

   Run the Python code in {work}/script-1/script.py

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The program has no menu route for this step. To repeat it, run the code.

4. calculate (step n4)

   Run the tool "calculate" with these settings: {"items":[{"name":"reference_sequences","expression":"55 - 16"}]}.
   - Code only: this step has no route in the program menus. Run it with the script or flow export.

   The harness recorded no manual route for this step.

5. run_script (step n5)

   Run the Python code in {work}/script-2/script.py

   • Code only: this step has no route in the program menus. Run it with the script or flow export.

   The program has no menu route for this step. To repeat it, run the code.

Figure

Run facts

The session

This is the session as the scientist sees it, in order. Decision cards show the answer that the script gave and where that answer comes from. Each step shows the program, its version, the input file hash and the outputs. Click a line to see more.

- Setup values:
Alignment:
- Alignment method (MAFFT) (algorithm): auto
- Trim the alignment (trim): false
Tree:
- Substitution model (model): TIM2e+I+G4
- Bootstrap type (bootstrap_type): ufboot
- Number of bootstrap replicates (replicates): 1000
- Outgroup (outgroup): Beltrania_rhombica_CBS_123.58
- Random seed (seed): 1
Ask the scientist: Largest gap fraction of a kept column (max_gap_fraction).
Fixed by the lab: Random seed (seed) = 1.
The harness fills these values into your tool calls automatically. If you give a different value, the harness logs a deviation and shows it to the scientist.
- Mode is now watch: you run the steps.

alignment={work}/align_sequences-1/aln.fasta
algorithm=auto
n_sequences=55
alignment_length=2352
gap_fraction=0.1441
constant_columns=1033
mean_pairwise_identity=0.9221
longest_input=2375
sequences_intact=1

report={work}/infer_tree-1/run.iqtree
seed=1
bootstrap_type=ufboot
bootstrap_replicates=1000
treefile={work}/infer_tree-1/run.treefile
consensus_tree={work}/infer_tree-1/run.contree
n_sequences=55
n_sites=2352
model=TIM2e+I+G4
log_likelihood=-16151.5762
tree_length=2.2758
constant_sites=1528
site_patterns=871

- You said what you will do next, but you did not call a tool. Do it now with a tool call, or give your final answer.

(((((((((((L240:0.0000000000,L106:0.0000000000):0.0000000000,Sporocadus_rosigena_CBS_182.50:0.0000000000):0.0000010018,L105:0.0000010018)100:0.0265892060,Sporocadus_sorbi_CBS_160.25:0.0152473927)100:0.0093212605,(((L158:0.0000000000,Sporocadus_kurdistanicus_CBS_143778:0.0000000000):0.0000000000,L181:0.0000000000):0.0000010018,L164:0.0000010018)100:0.0264475486)98:0.0080534050,(((Sporocadus_glandigenus_NBRC_32677:0.0000010018,Sporocadus_lichenicola_CBS_354.90:0.0004599663)82:0.0000419166,Sporocadus_lichenicola_CPC_24528:0.0000010018)100:0.0191904291,Sporocadus_cornicola_CBS_143889:0.0161401774)100:0.0182112664)89:0.0047037209,Sporocadus_cornii_MFLUCC_140467:0.0180877096)67:0.0247686332,(((Sporocadus_rotundatus_CBS_616.83:0.0392800340,(Sporocadus_microcyclus_CBS_887.68:0.0465354156,Sporocadus_biseptatus_CBS_110324:0.0394564254)100:0.0143233157)91:0.0020100518,Sporocadus_cotini_CBS_139966:0.0427952061)97:0.0048665804,((Sporocadus_italicus_MFLUCC_141196:0.0117428687,Sporocadus_incanus_CBS_123003:0.0000010018)100:0.0271773554,Sporocadus_mali_CBS_446.70:0.0395889323)79:0.0027790731)88:0.0039523258)39:0.0019122402,(Sporocadus_multiseptatus_CBS_143899:0.0467083341,(Sporocadus_trimorphus_CBS_114203:0.0339409127,Sporocadus_rosarum_CBS_113832:0.0306996158)99:0.0153595318)27:0.0038877101)99:0.0341540117,((((Seimatosporium_parasiticum_NBRC_32682:0.0038842630,Seimatosporium_physocarpi_CBS_139968:0.0000010018)100:0.0538736338,(((Seimatosporium_pistaciae_CBS_138865:0.0005201843,Seimatosporium_rosae_CBS_139823:0.0010178523)99:0.0042406707,Seimatosporium_germanicum_CBS_437.87:0.0079876607)100:0.0413537777,Seimatosporium_soli_CBS_941.69:0.0578404698)68:0.0075349385)54:0.0047834383,((Seimatosporium_vitis_Napa764:0.0002692068,((Seimatosporium_vitis-viniferae_CBS_123004:0.0000010018,P210:0.0000010018)78:0.0000010018,(Seimatosporium_vitis_MFLUCC_140051:0.0000010018,((((((L189:0.0000000000,P57:0.0000000000):0.0000000000,P56:0.0000000000):0.0000000000,L34:0.0000000000):0.0000000000,L33:0.0000000000):0.0000000000,P46:0.0000000000):0.0000010018,P60:0.0000010018)87:0.0005104445)30:0.0000022365)57:0.0012707320)100:0.0315439485,(Seimatosporium_luteosporum_CBS_142599:0.0169575527,(Seimatosporium_vitifusiforme_CBS_142600:0.0016696554,(Seimatosporium_marivanicum_CBS_143781:0.0005038755,(L112:0.0000010018,L111:0.0000010018)99:0.0009991955)98:0.0013436906)100:0.0109077088)100:0.0218988446)89:0.0064625867)81:0.0160650678,(Seimatosporium_discosioides_NBRC_104201:0.0623945916,Seimatosporium_botan_NBRC_104200:0.0447912097)100:0.0354491503)96:0.0211386314)94:0.0268067966,Beltrania_rhombica_CBS_123.58:0.5401182917,(((Allelochaeta_biseptata_CBS_131116:0.0861805929,Allelochaeta_fusispora_CBS_144172:0.0914671535)96:0.0182187247,(Sarcostroma_grevilleae_CBS_101.71:0.0409313224,(Sarcostroma_diversiseptatum_CBS_189.81:0.0288597626,Sarcostroma_restionis_CBS_118154:0.0202129794)100:0.0240730870)100:0.0427838059)100:0.0538767574,Diploceras_hypericinum_CBS_143885:0.1934874271)90:0.0230988869);

The final answer

The model wrote this answer. The harness shows it to the scientist after the review.

Settings used, from the decision record: Alignment method (MAFFT): auto · Substitution model: TIM2e+I+G4 · Bootstrap type: ufboot · Number of bootstrap replicates: 1000 · Outgroup: Beltrania_rhombica_CBS_123.58 · Random seed: 1.

Values that are not scored

• A trap value is the result of a wrong method, for example an unpaired test on paired data. A trap value in a main step means that the run used the wrong method. A trap value in a comparison run is correct, because the record keeps the scientist's choice.
• An optional value is a second result of the same method. The run can compute it or not.
• A reference value comes from a different program version or a check run by us. We show it for comparison.

Checks

Review findings

The review recorded 4 findings. A rule finding comes from a fixed check in the harness. A referee finding comes from a second model that reads the record. The harness shows the findings to the scientist with the final answer. The record does not mark a finding as fixed. Thus a finding from an early review round can apply to a draft that the model corrected later.

Numbers in the answer

The last claim check read 3 numbers in the answer. 3 numbers match a logged result. 0 numbers have no source in the record.

Deviations

The model did not try to change a choice of the scientist.

Failed tool calls

No tool call failed.

Data integrity

Each data file has the same SHA-256 hash now as at the time of the step that read it. Where the download script (fetch.sh) gives a hash, the file also has that hash. The run did not change the data.

A SHA-256 hash is a fingerprint of the file contents. If one byte of the file changes, the hash changes. The table shows the first 12 characters.

How to repeat it

Get the data. The script downloads the files and checks their SHA-256 hashes where it lists them.

CUVETTE_DATA={data} bash bench/papers/kanetis2022-iqtree-sporocadaceae/fetch.sh

Run the same case with Cuvette. The script gives the same answers from bench/papers/kanetis2022-iqtree-sporocadaceae/bench.yaml.

cuvette bench papers --papers kanetis2022-iqtree-sporocadaceae --models ollama:qwen3:8b

Repeat each step by hand in the program. For each step, the harness records a manual route: the menu path or the code that gives the same result. This list does not include comparison runs.

1. align_sequences (step n1)

   Run: mafft --auto <in>.fasta > <out>.fasta

   • <in>.fasta

     {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas

   • --auto = auto
   • Warning: If you keep the default , you get a different result.
   • Note: The tool also runs MAFFT with one thread and counts gaps and constant columns. The alignment itself is the same as the command line.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/checkout/catalog/phylo/scripts/align.sh auto {data}/kanetis2022-iqtree-sporocadaceae/concat_dush_subalign.fas {work}/align_sequences-1/aln.fasta

   The manual route uses the same method. The note in the route gives the known difference.

2. infer_tree (step n2)

   Run: iqtree3 -s <alignment> -m <model> -B <replicates> -seed <seed> -T 1

   • -s

     {work}/align_sequences-1/aln.fasta

   • -m = TIM2e+I+G4
   • -B = 1000
   • -o = Beltrania_rhombica_CBS_123.58
   • -seed = 1
   • Warning: If you keep the default MFP, you get a different result.
   • Warning: If you keep the default , you get a different result.
   • Warning: If you keep the default random, you get a different result.

   The manual route that the harness recorded

   /bin/sh {other volume}/tools/overnight/checkout/catalog/phylo/scripts/iqtree.sh /opt/homebrew/bin/iqtree3 infer --alignment {work}/align_sequences-1/aln.fasta --model TIM2e+I+G4 --bootstrap-type ufboot --replicates 1000 --outgroup Beltrania_rhombica_CBS_123.58 --seed 1

   The manual route gives the same numbers. An automatic test in Cuvette checks this.

Figure

Run facts