yogsoth-ai/de-anthropocentric-research-engine

select-experimental-baseline

Select fair SOTA/simple/oracle/control baselines with provenance and rationale matched to the experimental claim.

使い方

インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
必要なツール、認証情報、対応環境を原文で確認します。
入力と成果物を指定し、出力を資料と照合します。

npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill select-experimental-baseline

開始前の確認

導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。

リポジトリの原文

見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。

select-experimental-baseline

Purpose

Select fair SOTA/simple/oracle/control baselines with provenance and rationale matched to the experimental claim.

Input contract

yaml

required: [experimental_claim, candidate_baselines, protocol_context]
optional: [evidence, assumptions, prior_results]
constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]

Procedure

Validate the typed inputs and state the decision this operation must support.
Apply the declared operation to the named object; record intermediate values that affect interpretation.
Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.

Output contract

yaml

produces: [select_experimental_baseline_result, evidence_trace, uncertainties]
delta_fields: [evidence_updates, uncertainties]

Quality gates

Inputs are named scientific objects with compatible schemas.
Every material result has a derivation or source reference.
Fixed statistical criteria remain exact where applicable: $\alpha$ 0.05 and power 0.8.

Failure and counterexamples

Return a failed operation with the violated precondition when inputs are incomplete, assumptions are unsupported, or a counterexample defeats the result.