BixBench current item

bix-16-q1

Question

In the provided data, what gene symbol has the strongest negative Spearman correlation between its expression and essentiality?

Accepted answer
CDKN1A
Domain
crispr dependency

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
2.10M total		3/3
replicate 1 replicate 2 replicate 3
1.28M total
Codex GPT-5.6 Sol3/3
replicate 1 replicate 2 replicate 3
2.58M total		3/3
replicate 1 replicate 2 replicate 3
1.16M total
Codex GPT-5.6 Luna2/3
replicate 1 replicate 2 replicate 3
3.12M total		2/3
replicate 1 replicate 2 replicate 3
3.15M total
DeepSeek V4 Pro via Codex1/3
replicate 1 replicate 2 replicate 3
9.96M total		1/3
replicate 1 replicate 2 replicate 3
1.15M total
DeepSeek V4 Pro via Claude Codesuperseded1/3
replicate 1 replicate 2 replicate 3
2.92M total		1/3
replicate 1 replicate 2 replicate 3
1.50M total

Execution condition

Galaxy-API code with skills

Codex GPT-5.5

3 primary replicates
Codex GPT-5.5

replicate 1

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
634.5K
Output
5.9K
Galaxy historyRun trace
Codex GPT-5.5

replicate 2

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
542.8K
Output
4.5K
Galaxy historyRun trace
Codex GPT-5.5

replicate 3

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
924.4K
Output
4.3K
Galaxy historyRun trace

Codex GPT-5.6 Sol

3 primary replicates
Codex GPT-5.6 Sol

replicate 1

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
933.3K
Output
4.1K
Galaxy historyRun trace
Codex GPT-5.6 Sol

replicate 2

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
984.3K
Output
4.4K
Galaxy historyRun trace
Codex GPT-5.6 Sol

replicate 3

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
664.0K
Output
3.9K
Galaxy historyRun trace

Codex GPT-5.6 Luna

3 primary replicates
Codex GPT-5.6 Luna

replicate 1

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
815.9K
Output
9.8K
Galaxy historyRun trace
Codex GPT-5.6 Luna

replicate 2

fail

Why it missed

Answer extraction errorThe downloaded Galaxy table is byte-identical to the two passing replicates and its minimum coefficient is CDKN1A at -0.5234. The agent mis-sorted or misread that completed table and reported USP54.
AnswerUSP54
Workflow
Spearman correlation
Total tokens
1.26M
Output
11.9K
Galaxy historyRun trace
Codex GPT-5.6 Luna

replicate 3

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
1.05M
Output
8.9K
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.
AnswerCOX17
Workflow
Galaxy via BioBlendSciPySpearman correlation
Total tokens
4.94M
Output
40.2K
Galaxy historyRun trace
DeepSeek V4 Pro via Codex

replicate 2

pass
AnswerCDKN1A
Workflow
Galaxy historySciPySpearman correlation
Total tokens
1.81M
Output
17.3K
Galaxy historyRun trace
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.
AnswerCCND1
Workflow
Galaxy via BioBlendSpearman correlation
Total tokens
3.21M
Output
14.5K
Galaxy historyRun trace

DeepSeek V4 Pro via Claude CodeSuperseded

3 primary replicates
DeepSeek V4 Pro via Claude Code

replicate 1

pass
AnswerCDKN1A
Workflow
Spearman correlation
Total tokens
1.35M
Output
21.6K
Galaxy historyRun trace
DeepSeek V4 Pro via Claude Code

replicate 2

fail

Why it missed

Scientific interpretation errorThis run ranked the raw CRISPR gene-effect sign and selected CCND1. More negative gene-effect values mean stronger dependency, and applying that direction selects CDKN1A.
AnswerCCND1
Workflow
Spearman correlation
Total tokens
783.8K
Output
7.9K
Galaxy historyRun trace
DeepSeek V4 Pro via Claude Code

replicate 3

fail

Why it missed

Scientific interpretation errorThis run ranked the raw CRISPR gene-effect sign and selected CCND1. More negative gene-effect values mean stronger dependency, and applying that direction selects CDKN1A.
AnswerCCND1
Workflow
Spearman correlation
Total tokens
785.8K
Output
7.3K
Galaxy historyRun trace

Execution condition

Open-ended code with skills

Codex GPT-5.5

3 primary replicates
Codex GPT-5.5

replicate 1

pass
AnswerCDKN1A
Workflow
Local analysisSpearman correlationSciPymean summary
Total tokens
534.2K
Output
10.1K
Run trace
Codex GPT-5.5

replicate 2

pass
AnswerCDKN1A
Workflow
Local analysisSciPySpearman correlationmean summary
Total tokens
518.5K
Output
5.9K
Run trace
Codex GPT-5.5

replicate 3

pass
AnswerCDKN1A
Workflow
Local analysisSciPymean summarySpearman correlation
Total tokens
226.8K
Output
6.9K
Run trace

Codex GPT-5.6 Sol

3 primary replicates
Codex GPT-5.6 Sol

replicate 1

pass
AnswerCDKN1A
Workflow
Local analysis
Total tokens
418.9K
Output
6.2K
Run trace
Codex GPT-5.6 Sol

replicate 2

pass
AnswerCDKN1A
Workflow
Local analysis
Total tokens
245.8K
Output
4.8K
Run trace
Codex GPT-5.6 Sol

replicate 3

pass
AnswerCDKN1A
Workflow
Local analysis
Total tokens
500.1K
Output
8.2K
Run trace

Codex GPT-5.6 Luna

3 primary replicates
Codex GPT-5.6 Luna

replicate 1

pass
AnswerCDKN1A
Workflow
Local analysis
Total tokens
1.01M
Output
14.8K
Run trace
Codex GPT-5.6 Luna

replicate 2

pass
AnswerCDKN1A
Workflow
Local analysis
Total tokens
825.1K
Output
15.5K
Run trace
Codex GPT-5.6 Luna

replicate 3

fail

Why it missed

Essentiality direction was not convertedThis run ranked expression against the negative-going raw CRISPR gene-effect score and selected CCND1. Converting gene effect to positive-going essentiality changes the requested strongest negative correlation to CDKN1A.
AnswerCCND1
Workflow
Local analysis
Total tokens
1.32M
Output
16.7K
Run 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.
AnswerCCND1
Workflow
Local analysisSciPyscikit-learnmean summarySpearman correlation
Total tokens
338.2K
Output
11.8K
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.
AnswerCCND1
Workflow
Local analysisSciPyscikit-learnSpearman correlationmean summary
Total tokens
497.9K
Output
13.5K
Run trace
DeepSeek V4 Pro via Codex

replicate 3

pass
AnswerCDKN1A
Workflow
Local analysisSciPyscikit-learnSpearman correlation
Total tokens
309.1K
Output
10.0K
Run trace

DeepSeek V4 Pro via Claude CodeSuperseded

3 primary replicates
DeepSeek V4 Pro via Claude Code

replicate 1

pass
AnswerCDKN1A
Workflow
Local analysisSpearman correlationSciPy
Total tokens
561.3K
Output
12.1K
Run trace
DeepSeek V4 Pro via Claude Code

replicate 2

fail

Why it missed

Scientific interpretation errorThis run ranked the raw CRISPR gene-effect sign and selected CCND1. More negative gene-effect values mean stronger dependency, and applying that direction selects CDKN1A.
AnswerCCND1
Workflow
Local analysisSciPy
Total tokens
529.6K
Output
10.4K
Run trace
DeepSeek V4 Pro via Claude Code

replicate 3

fail

Why it missed

Scientific interpretation errorThis run ranked the raw CRISPR gene-effect sign and selected CCND1. More negative gene-effect values mean stronger dependency, and applying that direction selects CDKN1A.
AnswerCCND1
Workflow
Local analysisSciPy
Total tokens
410.6K
Output
5.1K
Run trace

bix-16-q1 · 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 0.39M tokens; previous website Galaxy averaged 0.86M; the new Galaxy runs averaged 0.98M, or 2.52× 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