Codex GPT-5.5
replicate 1
passUDT-only
Answer
-0.0603966860667375Workflow
Galaxy UDTPyDESeq2apeglm
- Total tokens
- 947.0K
- Output
- 11.3K
New token-optimization experiment
Three additional GPT-5.6 Sol Galaxy replicates are available separately. Previous results remain unchanged.
Question
Using the batch-corrected read counts with batch as a covariate in the design formula, perform a sex-specific (M vs F) differential expression analysis (abs lfc>0.5, basemean>10 and using lfc shrinkage), what is the log2 fold change of FAM138A? Use pydeseq2 with default shrinkage method.
Comparison
Pass counts and token totals across the same three replicates.
| Agent | Galaxy-API code | Open-ended code |
|---|---|---|
| Codex GPT-5.5 | 3/3 replicate 1 replicate 2 replicate 3 3.09M total | 3/3 replicate 1 replicate 2 replicate 3 7.37M total |
| Codex GPT-5.6 Sol | 3/3 replicate 1 replicate 2 replicate 3 3.69M total | 3/3 replicate 1 replicate 2 replicate 3 38.09M total |
| Codex GPT-5.6 Luna | 3/3 replicate 1 replicate 2 replicate 3 12.01M total | 3/3 replicate 1 replicate 2 replicate 3 33.89M total |
| DeepSeek V4 Pro via Codex | 1/3 replicate 1 replicate 2 replicate 3 206.76M total | 2/3 replicate 1 replicate 2 replicate 3 27.97M total |
| DeepSeek V4 Pro via Claude Codesuperseded | 3/3 replicate 1 replicate 2 replicate 3 5.91M total | 0/3 replicate 1 replicate 2 replicate 3 6.89M total |
Execution condition
Galaxy-API code with skills
Codex GPT-5.5
3 primary replicatesCodex GPT-5.5
replicate 2
passUDT-only
Answer
-0.06039668606673749Workflow
Galaxy UDTPyDESeq2apeglm
- Total tokens
- 1.06M
- Output
- 12.8K
Codex GPT-5.5
replicate 3
passUDT-only
Answer
-0.0603966860667375Workflow
Galaxy UDTPyDESeq2
- Total tokens
- 1.08M
- Output
- 21.2K
Codex GPT-5.6 Sol
3 primary replicatesCodex GPT-5.6 Sol
replicate 1
passUDT-only
Answer
-0.06039668606673749Workflow
Galaxy UDTPyDESeq2
- Total tokens
- 1.38M
- Output
- 11.4K
Codex GPT-5.6 Sol
replicate 2
passUDT-only
Answer
-0.06038358382893102Workflow
Galaxy UDTPyDESeq2
- Total tokens
- 751.6K
- Output
- 12.5K
Codex GPT-5.6 Sol
replicate 3
passUDT-only
Answer
-0.060396686066737489Workflow
Galaxy UDTPyDESeq2
- Total tokens
- 1.56M
- Output
- 9.7K
Codex GPT-5.6 Luna
3 primary replicatesCodex GPT-5.6 Luna
replicate 1
passUDT-only
Answer
-0.0603966860667375Workflow
Galaxy UDTPyDESeq2apeglm
- Total tokens
- 3.79M
- Output
- 27.2K
Codex GPT-5.6 Luna
replicate 2
passUDT-only
Answer
-0.06039668606673749Workflow
Galaxy UDTPyDESeq2apeglm
- Total tokens
- 5.07M
- Output
- 28.1K
Codex GPT-5.6 Luna
replicate 3
passUDT-only
Answer
-0.060383583828931144Workflow
Galaxy UDTPyDESeq2
- Total tokens
- 3.15M
- Output
- 30.1K
DeepSeek V4 Pro via Codex
3 primary replicatesDeepSeek V4 Pro via Codex
replicate 1
pass
Answer
-0.06039668606673749Workflow
Galaxy via BioBlendPyDESeq2AIC model selection
- Total tokens
- 5.42M
- Output
- 29.5K
DeepSeek V4 Pro via Codex
replicate 2
fail
Evaluation status
Manual review pendingThe evaluator marked this answer incorrect. The answer, workflow summary, usage, and available run records are linked, but a manual root-cause audit has not yet been added.
Answer
-0.0811399950077174Workflow
Galaxy via BioBlendPyDESeq2apeglm
- Total tokens
- 61.25M
- Output
- 110.3K
DeepSeek V4 Pro via Codex
replicate 3
failUDT + standard tools
Evaluation status
Manual review pendingThe evaluator marked this answer incorrect. The answer, workflow summary, usage, and available run records are linked, but a manual root-cause audit has not yet been added.
Answer
-0.0827864058663109Workflow
Galaxy via BioBlendPyDESeq2AIC model selectionSciPymedian summary
- Total tokens
- 140.10M
- Output
- 285.5K
DeepSeek V4 Pro via Claude CodeSuperseded
3 primary replicatesDeepSeek V4 Pro via Claude Code
replicate 1
passUDT-only
Answer
-0.06039668606673749Workflow
Galaxy UDTPyDESeq2apeglm
- Total tokens
- 2.31M
- Output
- 42.7K
DeepSeek V4 Pro via Claude Code
replicate 2
passUDT-only
Answer
-0.06039672801767835Workflow
Galaxy UDTPyDESeq2apeglm
- Total tokens
- 1.61M
- Output
- 16.1K
DeepSeek V4 Pro via Claude Code
replicate 3
passUDT-only
Answer
-0.060397Workflow
Galaxy UDTPyDESeq2apeglm
- Total tokens
- 1.99M
- Output
- 27.9K
Execution condition
Open-ended code with skills
Codex GPT-5.5
3 primary replicatesCodex GPT-5.5
replicate 1
pass
Answer
-0.0664352942951822Workflow
Local analysisPyDESeq2mean summarymedian summary
- Total tokens
- 2.38M
- Output
- 14.6K
Codex GPT-5.5
replicate 2
pass
Answer
-0.0603967697092Workflow
Local analysisPyDESeq2mean summary
- Total tokens
- 2.61M
- Output
- 17.4K
Codex GPT-5.5
replicate 3
pass
Answer
-0.060396769709177636Workflow
Local analysisPyDESeq2mean summary
- Total tokens
- 2.38M
- Output
- 12.8K
Codex GPT-5.6 Sol
3 primary replicatesCodex GPT-5.6 Sol
replicate 1
pass
Answer
-0.06039674813025112Workflow
Local analysis
- Total tokens
- 4.84M
- Output
- 12.0K
Codex GPT-5.6 Sol
replicate 2
pass
Answer
-0.060396769709177636Workflow
Local analysis
- Total tokens
- 5.17M
- Output
- 14.9K
Codex GPT-5.6 Sol
replicate 3
pass
Answer
-0.06039674813025112Workflow
Local analysis
- Total tokens
- 28.08M
- Output
- 31.1K
Codex GPT-5.6 Luna
3 primary replicatesCodex GPT-5.6 Luna
replicate 1
pass
Answer
-0.060396769709177636Workflow
Local analysis
- Total tokens
- 8.73M
- Output
- 30.1K
Codex GPT-5.6 Luna
replicate 2
pass
Answer
-0.060396748130251122Workflow
Local analysis
- Total tokens
- 23.09M
- Output
- 38.0K
Codex GPT-5.6 Luna
replicate 3
pass
Answer
-0.060396769709177636Workflow
Local analysis
- Total tokens
- 2.07M
- Output
- 15.8K
DeepSeek V4 Pro via Codex
3 primary replicatesDeepSeek V4 Pro via Codex
replicate 1
pass
Answer
-0.0603967697091776Workflow
Local analysisPyDESeq2SciPyAIC model selectionmean summary
- Total tokens
- 3.22M
- Output
- 29.8K
DeepSeek V4 Pro via Codex
replicate 2
pass
Answer
-0.06039674813025112Workflow
Local analysisPyDESeq2SciPymean summaryAIC model selection
- Total tokens
- 19.00M
- Output
- 51.1K
DeepSeek V4 Pro via Codex
replicate 3
fail
Evaluation status
Manual review pendingThe evaluator marked this answer incorrect. The answer, workflow summary, usage, and available run records are linked, but a manual root-cause audit has not yet been added.
Answer
-0.04793740610780156Workflow
Local analysisPyDESeq2mean summarySciPy
- Total tokens
- 5.74M
- Output
- 48.8K
DeepSeek V4 Pro via Claude CodeSuperseded
3 primary replicatesDeepSeek V4 Pro via Claude Code
replicate 1
fail
Why it missed
Resource-driven scientific changeAfter the full PyDESeq2 fit exceeded the 3 GiB memory limit, this run added a low-count gene filter. That changed the gene population used by apeglm and shifted the reported FAM138A coefficient.
Answer
-0.071997329736905Workflow
Local analysisPyDESeq2SciPyAIC model selectionmean summary
- Total tokens
- 2.99M
- Output
- 21.7K
DeepSeek V4 Pro via Claude Code
replicate 2
fail
Why it missed
Resource-driven scientific changeAfter the full PyDESeq2 fit exceeded the 3 GiB memory limit, this run added a low-count gene filter. That changed the gene population used by apeglm and shifted the reported FAM138A coefficient.
Answer
-0.048091Workflow
Local analysisPyDESeq2
- Total tokens
- 2.32M
- Output
- 18.7K
DeepSeek V4 Pro via Claude Code
replicate 3
fail
Why it missed
Resource-driven scientific changeAfter the full PyDESeq2 fit exceeded the 3 GiB memory limit, this run added a low-count gene filter. That changed the gene population used by apeglm and shifted the reported FAM138A coefficient.
Answer
-0.04917982789415693Workflow
Local analysismean summaryPyDESeq2SciPyapeglm
- Total tokens
- 1.58M
- Output
- 18.5K
bix-31-q2 · October 2026 · three additional replicates
GPT-5.6 Sol · token optimization
Galaxy-API code, high reasoning, Fast service. Previous runs are retained above.
Galaxy-API code · October 2026
replicate 1
Correct
Answer
-0.06039668606673749- Total tokens
- 795.8K
- Input
- 783.1K
- Cached input
- 741.8K
- Output
- 12.8K
Galaxy-API code · October 2026
replicate 2
Correct
Answer
-0.06039668606673749- Total tokens
- 594.9K
- Input
- 587.7K
- Cached input
- 552.8K
- Output
- 7.2K
Galaxy-API code · October 2026
replicate 3
Correct
Answer
-0.06039668606673749- Total tokens
- 696.1K
- Input
- 682.7K
- Cached input
- 639.9K
- Output
- 13.4K
Open-ended code averaged 12.70M tokens; previous website Galaxy averaged 1.23M; the new Galaxy runs averaged 0.70M, or 0.05× Open-ended code. Each mean covers three replicates of this same task with GPT-5.6 Sol.
Cached input is already included in input tokens. Full nested tool/job evidence is in each HF run's galaxy_execution_records.tar.gz, with an accompanying member index.