Data Analysis
geniml
86100Total Score
Core Capability
84 / 100
Functional Suitability
11 / 12
Reliability
9 / 12
Performance & Context
7 / 8
Agent Usability
14 / 16
Human Usability
8 / 8
Security
10 / 12
Maintainability
9 / 12
Agent-Specific
16 / 20
Medical Task
20 / 20 Passed
91You have many BED files and need numeric features for clustering, similarity search, or downstream supervised learning (e.g., ChIP-seq/ATAC-seq region sets)
4/4
87You want unsupervised embeddings of genomic regions to compare region sets across experiments (Region2Vec)
4/4
85Region2Vec: Word2vec-style unsupervised embeddings for genomic regions from tokenized BED data
4/4
85BEDspace: StarSpace-based joint embedding space for region sets and metadata labels; supports similarity search and cross-modal retrieval
4/4
85End-to-end case for Region2Vec: Word2vec-style unsupervised embeddings for genomic regions from tokenized BED data
4/4
Veto GatesRequired pass for any deployment consideration
Skill Veto✓ All 4 gates passed
✓
Operational Stability
System remains stable across varied inputs and edge cases
PASS✓
Structural Consistency
Output structure conforms to expected skill contract format
PASS✓
Result Determinism
Equivalent inputs produce semantically equivalent outputs
PASS✓
System Security
No prompt injection, data leakage, or unsafe tool use detected
PASSResearch Veto✅ PASS — Applicable
| Dimension | Result | Detail |
|---|---|---|
| Scientific Integrity | PASS | The archived review kept this workflow anchored to supplied data fields and observable execution behavior, not fabricated results. |
| Practice Boundaries | PASS | The archived review kept this package within Machine learning toolkit for genomic interval (BED) data; use it when you need to tokenize..., not freeform inference detached from source data. |
| Methodological Ground | PASS | The archived evaluation treated the workflow as method-linked rather than ad hoc. |
| Code Usability | PASS | The legacy audit did not record a code-usability failure in the packaged analysis path. |
Core Capability84 / 100 — 8 Categories
Functional Suitability
Functional suitability was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
11 / 12
92%
Reliability
Related legacy finding for geniml: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
9 / 12
75%
Performance & Context
The archived review left minor headroom in how this analysis workflow scales across heavier contexts.
7 / 8
88%
Agent Usability
Agent usability was strong, but the workflow could surface its entry conditions a little more directly.
14 / 16
88%
Human Usability
The legacy audit gave full marks to human usability for this package.
8 / 8
100%
Security
The packaged workflow stayed safe overall, with only a small remaining deduction around boundary signaling.
10 / 12
83%
Maintainability
The analysis package is maintainable overall, though the archived score suggests modest cleanup headroom.
9 / 12
75%
Agent-Specific
The archived deduction in agent specific traces back to: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
16 / 20
80%
Core Capability Total84 / 100
Medical TaskExecution Average: 86.6 / 100 — Assertions: 20/20 Passed
91
Canonical
You have many BED files and need numeric features for clustering, similarity search, or downstream supervised learning (e.g., ChIP-seq/ATAC-seq region sets)
4/4 ✓
87
Variant A
You want unsupervised embeddings of genomic regions to compare region sets across experiments (Region2Vec)
4/4 ✓
85
Edge
Region2Vec: Word2vec-style unsupervised embeddings for genomic regions from tokenized BED data
4/4 ✓
85
Variant B
BEDspace: StarSpace-based joint embedding space for region sets and metadata labels; supports similarity search and cross-modal retrieval
4/4 ✓
85
Stress
End-to-end case for Region2Vec: Word2vec-style unsupervised embeddings for genomic regions from tokenized BED data
4/4 ✓
91
Canonical✅ Pass
You have many BED files and need numeric features for clustering, similarity search, or downstream supervised learning (e.g., ChIP-seq/ATAC-seq region sets)
You have many BED files and need numeric features for clustering,... remained tied to the documented analysis contract even when the preserved evidence centered on instructions instead of a full rerun.
Basic 36/40|Specialized 55/60|Total 91/100
✅A1The geniml output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
87
Variant A✅ Pass
You want unsupervised embeddings of genomic regions to compare region sets across experiments (Region2Vec)
This variant a case stayed within the packaged analysis boundary and kept a reviewable task contract.
Basic 34/40|Specialized 53/60|Total 87/100
✅A1The geniml output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
85
Edge✅ Pass
Region2Vec: Word2vec-style unsupervised embeddings for genomic regions from tokenized BED data
The archived run treated Region2Vec: Word2vec-style unsupervised embeddings for genomic... as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 33/40|Specialized 52/60|Total 85/100
✅A1The geniml output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
85
Variant B✅ Pass
BEDspace: StarSpace-based joint embedding space for region sets and metadata labels; supports similarity search and cross-modal retrieval
BEDspace: StarSpace-based joint embedding space for region sets and... remained an analysis-style extraction path whose value came from structured data capture rather than a freeform narrative response.
Basic 32/40|Specialized 53/60|Total 85/100
✅A1The geniml output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
85
Stress✅ Pass
End-to-end case for Region2Vec: Word2vec-style unsupervised embeddings for genomic regions from tokenized BED data
This stress case stayed within the packaged analysis boundary and kept a reviewable task contract.
Basic 29/40|Specialized 56/60|Total 85/100
✅A1The geniml output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
Medical Task Total86.6 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode A
- Static quality score is 84/100 and dynamic average is 78.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: No script verification was applicable