alternative-hypothesis-check

스타11

포크1

업데이트2026년 2월 22일 19:50

Use when analyzing results in Type D or Type H projects before making mechanistic or causal claims — requires systematic exclusion of confounders, batch effects, technical noise, and other alternative explanations

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

출처

EvoClaw

EvoClaw/amplify

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Alternative Hypothesis Check

Discipline layer skill. Active during Phase 4–5 for Type D and Type H projects.

Iron Law

NO MECHANISM CLAIMS WITHOUT EXCLUDING ALTERNATIVE EXPLANATIONS

Systematic Check

For each major finding, systematically check:

□ Confounders — variables that could explain the association independently of your proposed mechanism
□ Batch effects [bioinformatics] — technical variation masquerading as biology (plate, lane, date, operator)
□ Technical noise — measurement artifacts, instrument drift, reagent lot differences
□ Sample selection bias — non-random inclusion criteria that correlate with the outcome
□ Multiple testing inflation — testing many hypotheses means some will be significant by chance; confirm FDR/Bonferroni was applied
□ Correlation ≠ causation — temporal precedence, dose-response, and intervention evidence must be present before causal language is used

When an Alternative Explanation Cannot Be Excluded

If an alternative explanation cannot be excluded:

→ It must be stated as a limitation in the paper → Language must be weakened ("associated with" not "causes") → It cannot be presented as a mechanistic finding

Checklist Format

For each finding, produce a table:

Finding	Alternative checked	Excluded?	Evidence
...	Confounder X	Yes / No	...

Rationalization Firewall

You will hear yourself say...	Reality check
"The effect is too strong to be confounding"	Strong effects can still be confounded. Check anyway.
"We controlled for the obvious variables"	Obvious to you. What about reviewer #2's favorite confounder?
"Correlation is enough for this paper"	Correlation is enough only if you DON'T claim mechanism.
"Batch correction was applied"	Did you verify it worked? Show before/after.

이 저장소의 다른 Skills

같은 저장소

evaluation-protocol-design

EvoClaw/amplify

Use when designing the evaluation protocol for a method development project — locks primary metrics, datasets, seeds, statistical tests, and baseline list into an immutable contract

2026-02-2411

experiment-execution

EvoClaw/amplify

Use when G2 (plan freeze) and G3 (execution readiness) gates have passed — handles all implementation, baseline reproduction, experimentation, and iteration for both Type M and Type D projects; this is Phase 4

2026-02-2411

method-framework-design

EvoClaw/amplify

Use when research direction is validated (G1 passed) and the project needs method design, analysis framework, evaluation protocol, or story line — this is Phase 3 and must complete before any code or experiments

2026-02-2411

multi-round-deliberation

EvoClaw/amplify

Reusable protocol for multi-agent discussions that iterate until convergence. Used by results-integration (Phase 5) and paper-writing (Phase 6) to ensure discussions actually resolve issues rather than just noting them.

2026-02-2411

paper-writing

EvoClaw/amplify

Use when and ONLY when the user explicitly requests paper writing and G4 (write-ready) gate has passed — handles LaTeX structure, senior-level writing, reference verification, and iterative refinement

2026-02-2411

problem-validation

EvoClaw/amplify

Use when Phase 1 (research-direction-exploration) is complete and G1 gate has passed — subjects the research problem to adversarial defense-style questioning, classifies project intent, re-evaluates venue target, and produces a final feasibility ruling before any method design begins

2026-02-2411

name	alternative-hypothesis-check
description	Use when analyzing results in Type D or Type H projects before making mechanistic or causal claims — requires systematic exclusion of confounders, batch effects, technical noise, and other alternative explanations

Alternative Hypothesis Check

Discipline layer skill. Active during Phase 4–5 for Type D and Type H projects.

Iron Law

NO MECHANISM CLAIMS WITHOUT EXCLUDING ALTERNATIVE EXPLANATIONS

Systematic Check

For each major finding, systematically check:

□ Confounders — variables that could explain the association independently of your proposed mechanism
□ Batch effects [bioinformatics] — technical variation masquerading as biology (plate, lane, date, operator)
□ Technical noise — measurement artifacts, instrument drift, reagent lot differences
□ Sample selection bias — non-random inclusion criteria that correlate with the outcome
□ Multiple testing inflation — testing many hypotheses means some will be significant by chance; confirm FDR/Bonferroni was applied
□ Correlation ≠ causation — temporal precedence, dose-response, and intervention evidence must be present before causal language is used

When an Alternative Explanation Cannot Be Excluded

If an alternative explanation cannot be excluded:

→ It must be stated as a limitation in the paper → Language must be weakened ("associated with" not "causes") → It cannot be presented as a mechanistic finding

Checklist Format

For each finding, produce a table:

Finding	Alternative checked	Excluded?	Evidence
...	Confounder X	Yes / No	...

Rationalization Firewall

You will hear yourself say...	Reality check
"The effect is too strong to be confounding"	Strong effects can still be confounded. Check anyway.
"We controlled for the obvious variables"	Obvious to you. What about reviewer #2's favorite confounder?
"Correlation is enough for this paper"	Correlation is enough only if you DON'T claim mechanism.
"Batch correction was applied"	Did you verify it worked? Show before/after.