BixBench current item

bix-27-q5

Question

After performing principal component analysis (PCA) with 100 components on the log10-transformed gene expression matrix (with pseudocount of 1, samples as rows and genes as columns), what percentage of the total variance in the dataset is explained by the first principal component (reported as a percentage between 0 and 100)?

Accepted answer
(55,56)
Domain
expression matrix pca

Comparison

Pass counts and token totals across the same three replicates.

AgentGalaxy-API codeOpen-ended code
Codex GPT-5.53/3
replicate 1 replicate 2 replicate 3
2.85M total		3/3
replicate 1 replicate 2 replicate 3
813.6K total
Codex GPT-5.6 Sol3/3
replicate 1 replicate 2 replicate 3
2.66M total		3/3
replicate 1 replicate 2 replicate 3
678.4K total
Codex GPT-5.6 Luna3/3
replicate 1 replicate 2 replicate 3
25.67M total		2/3
replicate 1 replicate 2 replicate 3
1.04M total
DeepSeek V4 Pro via Codex2/3
replicate 1 replicate 2 replicate 3
15.08M total		2/3
replicate 1 replicate 2 replicate 3
6.54M total
DeepSeek V4 Pro via Claude Codesuperseded2/3
replicate 1 replicate 2 replicate 3
10.92M total		1/3
replicate 1 replicate 2 replicate 3
1.81M total

Execution condition

Galaxy-API code with skills

Codex GPT-5.5

3 primary replicates
Codex GPT-5.5

replicate 1

passUDT-only
Answer55.9711502411118%
Workflow
Galaxy UDTPCAscikit-learnmean summary
Total tokens
1.09M
Output
8.2K
Galaxy historyRun trace
Codex GPT-5.5

replicate 2

passUDT-only
Answer55.9711502411%
Workflow
Galaxy UDTPCAscikit-learn
Total tokens
1.01M
Output
15.6K
Galaxy historyRun trace
Codex GPT-5.5

replicate 3

passUDT-only
Answer55.9711502411%
Workflow
Galaxy UDTPCAscikit-learn
Total tokens
747.9K
Output
8.5K
Galaxy historyRun trace

Codex GPT-5.6 Sol

3 primary replicates
Codex GPT-5.6 Sol

replicate 1

passUDT-only
Answer55.971150241111815%
Workflow
Galaxy UDTPCAscikit-learn
Total tokens
698.1K
Output
9.7K
Galaxy historyRun trace
Codex GPT-5.6 Sol

replicate 2

passUDT-only
Answer55.971150241111815%
Workflow
Galaxy UDTPCAscikit-learn
Total tokens
1.08M
Output
11.2K
Galaxy historyRun trace
Codex GPT-5.6 Sol

replicate 3

passUDT-only
Answer55.971150241111765%
Workflow
Galaxy UDTPCAscikit-learnSciPymean summary
Total tokens
882.4K
Output
9.7K
Galaxy historyRun trace

Codex GPT-5.6 Luna

3 primary replicates
Codex GPT-5.6 Luna

replicate 1

passUDT + standard tools
Answer55.9711502411118%
Workflow
Csv To TabularColumn Remove By HeaderTp Cut Toolmore stepsPCAscikit-learn
Total tokens
7.84M
Output
42.5K
Galaxy historyRun trace
Codex GPT-5.6 Luna

replicate 2

pass
Answer55.9712069607%
Workflow
Convert Characters1Column Remove By HeaderSelect columnsmore stepsSklearn PcaSummary statistics
Total tokens
15.10M
Output
45.9K
Galaxy historyRun trace
Codex GPT-5.6 Luna

replicate 3

passUDT-only
Answer55.9711502411118%
Workflow
Galaxy UDTPCAscikit-learn
Total tokens
2.73M
Output
24.2K
Galaxy historyRun trace

DeepSeek V4 Pro via Codex

3 primary replicates
DeepSeek V4 Pro via Codex

replicate 1

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.
Answernot produced
Workflow
Galaxy via BioBlendPCA
Total tokens
1.96M
Output
10.6K
Galaxy historyRun trace
DeepSeek V4 Pro via Codex

replicate 2

pass
Answer55.97%
Workflow
Galaxy via BioBlendPCAscikit-learn
Total tokens
7.73M
Output
43.1K
Galaxy historyRun trace
DeepSeek V4 Pro via Codex

replicate 3

pass
Answer55.97%
Workflow
Galaxy via BioBlendPCAscikit-learn
Total tokens
5.39M
Output
36.9K
Galaxy historyRun trace

DeepSeek V4 Pro via Claude CodeSuperseded

3 primary replicates
DeepSeek V4 Pro via Claude Code

replicate 1

pass
Answer55.97%
Workflow
Table ComputeDatamash TransposeSklearn PcaPCAscikit-learn
Total tokens
5.58M
Output
51.5K
Galaxy historyRun trace
DeepSeek V4 Pro via Claude Code

replicate 2

failUDT + standard tools

Why it missed

Sample identity choiceThis run kept all 222 expression columns even though companion metadata identifies conflicting duplicate project IDs. It returned 56.47%; excluding the ambiguous identities gives about 55.97%.
Answer56.47%
Workflow
Datamash TransposeCsv To TabularConvert Characters1more stepsscikit-learnSciPy
Total tokens
2.87M
Output
29.3K
Galaxy historyRun trace
DeepSeek V4 Pro via Claude Code

replicate 3

passUDT-only
Answer55.97%
Workflow
Galaxy UDTPCAmean summarymedian summaryscikit-learnSciPy
Total tokens
2.46M
Output
30.2K
Galaxy historyRun trace

Execution condition

Open-ended code with skills

Codex GPT-5.5

3 primary replicates
Codex GPT-5.5

replicate 1

pass
Answer55.971150241111779%
Workflow
Local analysisPCAmean summaryscikit-learnSciPy
Total tokens
200.1K
Output
5.0K
Run trace
Codex GPT-5.5

replicate 2

pass
Answer55.971150241111644%
Workflow
Local analysisPCAscikit-learnSciPy
Total tokens
316.6K
Output
4.4K
Run trace
Codex GPT-5.5

replicate 3

pass
Answer55.9711502411%
Workflow
Local analysisPCAmean summaryscikit-learnSciPy
Total tokens
296.9K
Output
6.2K
Run trace

Codex GPT-5.6 Sol

3 primary replicates
Codex GPT-5.6 Sol

replicate 1

pass
Answer55.97115024111176%
Workflow
Local analysis
Total tokens
273.6K
Output
4.4K
Run trace
Codex GPT-5.6 Sol

replicate 2

pass
Answer55.971150241111744%
Workflow
Local analysis
Total tokens
185.9K
Output
3.4K
Run trace
Codex GPT-5.6 Sol

replicate 3

pass
Answer55.9711502411117%
Workflow
Local analysis
Total tokens
218.9K
Output
3.8K
Run trace

Codex GPT-5.6 Luna

3 primary replicates
Codex GPT-5.6 Luna

replicate 1

pass
Answer55.9711502411117%
Workflow
Local analysis
Total tokens
412.5K
Output
9.8K
Run trace
Codex GPT-5.6 Luna

replicate 2

pass
Answer55.971150241111779%
Workflow
Local analysis
Total tokens
330.9K
Output
10.0K
Run trace
Codex GPT-5.6 Luna

replicate 3

fail

Why it missed

Conflicting sample identities were retainedThis run kept all 222 expression columns even though companion metadata identifies conflicting duplicate project IDs. It returned 56.47%; excluding those ambiguous identities gives the accepted value near 55.97%.
Answer56.4717047395748%
Workflow
Local analysis
Total tokens
300.5K
Output
9.6K
Run trace

DeepSeek V4 Pro via Codex

3 primary replicates
DeepSeek V4 Pro via Codex

replicate 1

pass
Answer55.97115024111176%
Workflow
Local analysisPCASciPyscikit-learnmean summaryPearson correlation
Total tokens
1.30M
Output
22.2K
Run trace
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.
Answer56.4717047396%
Workflow
Local analysisPCASciPyscikit-learnmean summaryPearson correlation
Total tokens
4.57M
Output
40.4K
Run trace
DeepSeek V4 Pro via Codex

replicate 3

pass
Answer55.97115024111174%
Workflow
Local analysisPCAmean summarySciPyscikit-learn
Total tokens
669.3K
Output
14.9K
Run trace

DeepSeek V4 Pro via Claude CodeSuperseded

3 primary replicates
DeepSeek V4 Pro via Claude Code

replicate 1

fail

Why it missed

Sample identity choiceThis run kept all 222 expression columns despite conflicting duplicate project IDs in the companion metadata, producing 56.47% instead of about 55.97%.
Answer56.471704739574605%
Workflow
Local analysisPCAscikit-learn
Total tokens
348.3K
Output
2.6K
Run trace
DeepSeek V4 Pro via Claude Code

replicate 2

pass
Answer55.9712%
Workflow
Local analysismean summaryscikit-learnPCA
Total tokens
807.6K
Output
18.9K
Run trace
DeepSeek V4 Pro via Claude Code

replicate 3

fail

Why it missed

Duplicate-sample handlingThis run combined duplicate project IDs rather than excluding the conflicting identities, producing 56.02% instead of the accepted 55.97%.
Answer56.0181%
Workflow
Local analysisPCAmean summaryscikit-learnSciPy
Total tokens
656.6K
Output
12.6K
Run trace

bix-27-q5 · October 2026 · three additional replicates

GPT-5.6 Sol · token optimization

Galaxy-API code, high reasoning, Fast service. Previous runs are retained above.

Open-ended code averaged 0.23M tokens; previous website Galaxy averaged 0.89M; the new Galaxy runs averaged 0.81M, or 3.56× 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.

Optimization overview and all 150 runs