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☆ 642026年10月8日 更新
Builds or audits a literature review: evidence map, closest prior work, gap verdict, and synthesis plan. Use to check whether a contribution is novel, map what a literature establishes, or organize a review; systematic reviews get a protocol scaffold.
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☆ 642026年10月8日 更新
Designs and diagnoses list experiments (the item count technique): whether indirect measurement is warranted, control-list construction, design variants, estimators and assumption tests in the list package, and power. Use when measuring a sensitive item or debugging an implausible prevalence estimate.
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☆ 642026年10月8日 更新
Use when a task needs the judgment of a Data Warehousing Specialist — defining the grain of a fact table before modeling it, choosing a slowly changing dimension (SCD) type for a dimension attribute, designing an incremental ETL/ELT load strategy against a full-refresh alternative, resolving a conformed-dimension conflict across source systems, or diagnosing why a BI report's numbers don't reconcile to the source system.
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。
wonsukchoi/domain-experts☆ 202026年10月5日 更新
Process and analyze single-cell ATAC-seq data with Signac, ArchR, SnapATAC2, or Cell Ranger ATAC. Use when handling 10X scATAC or 10X Multiome (paired RNA+ATAC) data, performing per-cell QC, choosing between ArchR/Signac/SnapATAC2 ecosystems, building per-cluster consensus peaksets, integrating with paired scRNA-seq, doublet detection (AMULET vs ArchR vs scDblFinder), or running pseudobulk differential accessibility per cluster.
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。
lilinji/GeneTind-Life-Skills☆ 142026年8月21日 更新
Process and analyze single-cell ATAC-seq data with Signac, ArchR, SnapATAC2, or Cell Ranger ATAC. Use when handling 10X scATAC or 10X Multiome (paired RNA+ATAC) data, performing per-cell QC, choosing between ArchR/Signac/SnapATAC2 ecosystems, building per-cluster consensus peaksets, integrating with paired scRNA-seq, doublet detection (AMULET vs ArchR vs scDblFinder), or running pseudobulk differential accessibility per cluster.
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。
peacezha/HPClaw☆ 32026年10月11日 更新