engineering-config-grading
Featured(Proposal, unverified) Grade reproducibility-relevant engineering configuration items (hyperparameter search range, compute budget, seed handling, dataset splits) on a complete/partial/none scale, requiring the grader to first define what "complete" means per item before judging against it. Use this after study-design-tool-gate has dispatched an ML/CS engineering paper here; this is a graded QUALITY judgment, distinct from dual-column-self-check's binary Yes/No/NA self-audit checklists.
Install
Quality Score: 94/100
Skill Content
Details
- Author
- yogsoth-ai
- Repository
- yogsoth-ai/de-anthropocentric-research-engine
- Created
- 6 months ago
- Last Updated
- 1 weeks ago
- Language
- HTML
- License
- Apache-2.0
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
engineering-config-grading
(Proposal, unverified) Grade reproducibility-relevant engineering configuration items (hyperparameter search range, compute budget, seed handling, dataset splits) on a complete/partial/none scale, requiring the grader to first define what "complete" means per item before judging against it. Use this after study-design-tool-gate has dispatched an ML/CS engineering paper here; this is a graded QUALITY judgment, distinct from dual-column-self-check's binary Yes/No/NA self-audit checklists.
reforms-grading
Tactic: Grade an ML/CS paper's reproducibility configuration reporting as complete, partial, or none after checking that clinical appraisal tools do not apply. Use when the question is whether the work can be rerun.
reforms-grading
Tactic: Grade an ML/CS paper's reproducibility configuration reporting as complete, partial, or none after checking that clinical appraisal tools do not apply. Use when the question is whether the work can be rerun.