Reads a model's own uncertainty from token log-probabilities: collecting and aggregating label logprobs, confidence tiers and margins for triage, calibration against human labels (ECE, Brier, reliability diagrams), downstream use, and reproducibility. Use for per-item classifier confidence or routing low-confidence cases to human review; codebook and validation design go to text-classification.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Audit a methods section against a 45-item checklist drawn from the APSA Experimental Section rubric, JARS-Quant, CONSORT, and DA-RT. Use before submission or archiving, or to document a pre-analysis-plan deviation.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Run one consequential, contestable decision through a deliberative committee of GPT-6 Astra and Claude Opus, chaired by fable (default), astra, opus, or sol. Not for factual lookups, brainstorming, routine implementation, independent-coder reliability, or final professional judgment. Use when several options are defensible and the two model families should propose, critique, revise, and cross-rank under a predeclared rubric.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Drafts or audits a scientific paper's introduction: real-world motivation, evidence audit, theory-to-if-then funnel with a named estimand, bridges across experiments, and calibrated contributions. Use to write, frame, or critique an introduction.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Orchestrate complex work from an active gpt-6-astra or gpt-6.1-sol Codex session. The detected lead owns decomposition, integration, and verification; Astra keeps the hardest reasoning in the lead, while Sol escalates unusually difficult units to Astra. Both route bounded work to Sol at medium effort, mechanical work to Luna, and can use a cross-vendor Claude peer. Not for routine single-context work. Use when the user explicitly asks to orchestrate, delegate, fan out, parallelize, assign subagents, obtain independent checks, or have Codex act as tech lead.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Run a pre-submission manuscript audit covering argument, numerics, references, writing, figures, methods, preregistration, and replication readiness. Add --codex for a cross-model pass in which Codex and Claude review independently and verify each other's findings.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Typeset a working paper or journal submission in house-style LaTeX from Markdown, Word, TeX, ODT, RTF, or HTML. Use to convert drafts, build PDFs, or prepare journal-specific spacing, limits, anonymization, disclosures, and citations.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Writes or reviews a pre-analysis plan before data collection: registry choice (OSF, AEA, AsPredicted, registered reports), locked models and decision rules, code run on simulated data, contingencies, and deviation records. Use when drafting or auditing a pre-registration or PAP, choosing a registry, or handling a deviation.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Organize an author's response to peer review: extract every referee point, order the revision by dependency, flag possible pushbacks, and build the response-letter skeleton the author fills in. Use for revise-and-resubmit planning, response letters, or checking every point was answered.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Plans a research project as a durable decision map, resolving one design decision per session until the design is defensible and pre-registerable. Use at project start, when a design has more open decisions than one conversation holds, or when planning keeps restarting. Not for running analyses or writing the paper.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Audit fielded survey response data for registered elements, data quality, bot and AI-automation screening, and sample integrity, and emit an appendix-ready quality report. Use at soft launch or after fielding, before outcomes are analyzed.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Designs survey instruments: question wording, scales and index reliability, flow and treatment placement, pretesting, attention and speeding rules, and sensitive questions. Use when writing or revising survey questions, choosing scales, ordering blocks, or planning a pilot.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
Advises on setting up and validating topic models for survey and experimental text: discovery vs. measurement, STM/LDA/BERTopic choice, preprocessing, covariate formulas, choosing K across coherence, FREX, held-out likelihood, and residuals, validating topics against human coding, robustness, and reporting. Coding against a fixed codebook goes to text-classification.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
OCR scanned or image-only corpora with vision-language models in three phases: `evaluate` picks a system by measured CER/WER against stratified human ground truth, `run` builds the production pipeline, and `clean` corrects raw OCR with LLM and rule-based passes, diagnostics, and span-level provenance. Born-digital documents with a text layer go to $doc-to-markdown.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新
House rules and craft for LaTeX Beamer decks (storyboarding, slide prose, frame budgets, layout, XeLaTeX and Korean fonts, color, figures, Overleaf hygiene, build QA). Use to write, edit, review, or build a Beamer deck.
日本語の概要は準備中です。原文の説明を表示しています。
scdenney/open-science-skills☆ 652026年10月8日 更新