القائمة
Assess translational gaps between preclinical models and human diseases to predict clinical failure risks
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اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/majiayu000/claude-skill-registry --skill translational-gap-analyzerيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
LLM token logprobs and calibration. Per-decision confidence, ECE, Brier, reliability diagrams, low-confidence triage.
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
回顾最近 N 天的 Claude Code 使用记录——扫描原始会话数据，按主题分组汇总"我都做了什么"，并从个人操作系统视角输出模式、风险与增删建议。当用户说 /recap、"看看我这几天做了什么"、"回顾一下我最近的会话"、"这两天我用 claude 干了啥"、"活动回顾" 时使用。
استنادا إلى تصنيف SOC المهني
عرض SKILL.md
| name | translational-gap-analyzer |
| description | Assess translational gaps between preclinical models and human diseases to predict clinical failure risks |
| version | 1.0.0 |
| category | Pharma |
| tags | [] |
| author | AIPOCH |
| license | MIT |
| status | Draft |
| risk_level | Medium |
| skill_type | Tool/Script |
| owner | AIPOCH |
| reviewer | |
| last_updated | 2026-02-06 |
ID: 209
Assesses the "translational gap" between basic research models (such as mice, zebrafish, cell lines) and human diseases, providing early warning of clinical translation failure risks. This system helps researchers identify potential translational barriers in preclinical research and improve clinical trial success rates through multi-dimensional analysis.
# Full assessment report
python scripts/main.py --model <model_type> --disease <disease_name> --full
# Quick risk assessment
python scripts/main.py --model <model_type> --disease <disease_name> --quick
# Compare multiple models
python scripts/main.py --models mouse,rat,primate --disease <disease_name> --compare
# Specify focus areas
python scripts/main.py --model mouse --disease "Alzheimer's" --focus metabolism,immune
| Argument | Description | Required |
|---|---|---|
--model | Model type (mouse, rat, zebrafish, cell_line, organoid, primate) | Yes (unless --models) |
--models | Multi-model comparison mode, comma-separated | No |
--disease | Disease name or MeSH ID | Yes |
--focus | Focus areas, comma-separated (anatomy, physiology, metabolism, immune, genetics, behavior) | No |
--full | Generate full assessment report | No |
--quick | Quick risk assessment mode | No |
--compare | Multi-model comparison mode | No |
--output | Output file path | No |
--format | Output format (json, markdown, table) | No |
{
"model": "mouse",
"disease": "Alzheimer's Disease",
"overall_gap_score": 6.8,
"risk_level": "HIGH",
"dimensions": {
"genetics": {"score": 8.5, "concerns": ["APOE4 differences", "Different tau pathology patterns"]},
"physiology": {"score": 7.0, "concerns": ["Brain structure differences", "Lifespan differences"]},
"metabolism": {"score": 6.5, "concerns": ["Significant drug metabolism differences"]},
"immune": {"score": 5.5, "concerns": ["Microglia functional differences", "Different neuroinflammation patterns"]},
"behavior": {"score": 6.0, "concerns": ["Limitations in cognitive assessment methods"]}
},
"clinical_failure_predictors": [
"Immune-related mechanism research may not translate",
"Drug clearance rate differences may lead to inappropriate dosing"
],
"recommendations": [
"Consider using humanized mouse models",
"Add non-human primate validation experiments",
"Focus on peripheral immune and central immune interactions"
]
}
| Model | Applicable Scenarios | Typical Gaps |
|---|---|---|
| mouse | Genetic manipulation, basic research | Immune, metabolism, brain structure |
| rat | Behavioral studies, cardiovascular | Cognition, drug metabolism |
| zebrafish | Development, high-throughput screening | Anatomy, physiology |
| cell_line | Molecular mechanisms | Microenvironment, systemic |
| organoid | Human-specific research | Maturity, vascularization |
| primate | Preclinical validation | Cost, ethics |
SKILL.md - This filescripts/main.py - Main analysis script| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
# Python dependencies
pip install -r requirements.txt