'reproducibility' 검색 결과

Reads model uncertainty from token log-probabilities. Covers collecting logprobs and aggregating multi-token labels, confidence tiers and margins for triage, calibration assessment with ECE, Brier scores, and reliability diagrams against human labels, responsible downstream use of confidence, and reproducibility archives. Use when the user asks about classifier confidence by item, logprobs, top-k tokens, calibration, ECE, Brier, reliability diagrams, or routing low-confidence cases to human review. Codebook and validation design go to text-classification.

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Designs publication figures for social-science manuscripts. Covers chart choice, axes and scales, color and accessibility, legend order, captions that carry the title, and script-based reproducibility. Use when making, revising, or critiquing a figure for a paper, such as a coefficient plot, small multiples, a distribution, a trend, a map, or a network. Finished figure sets go to figure-table-audit for end-stage QA.

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Design and format publication-quality tables. Use for column order, row grouping, notes, statistical precision, accessibility, and reproducibility.

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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.

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Nature-style chemistry manuscript reviewer skill for testing synthesis, catalysis, chemical biology, molecular/materials chemistry and analytical claims against identity, purity, controls, selectivity, mechanism, scope, reproducibility and quantitative comparison.

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Manage R package dependencies using renv for reproducible environments. Covers initialization, snapshot/restore workflow, troubleshooting common issues, and CI/CD integration. Use when initializing dependency management for a new R project, adding or updating packages, restoring an environment on a new machine, troubleshooting restore failures, or integrating renv with CI/CD pipelines.

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Create a Dockerfile for R projects using rocker base images. Covers system dependency installation, R package installation, renv integration, and optimized layer ordering for fast rebuilds. Use when containerizing an R application or analysis, creating reproducible R environments, deploying R-based services (Shiny, Plumber, MCP server), or setting up consistent development environments across machines.

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Guidelines for structuring and documenting Jupyter notebooks for reproducibility and clarity.

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MATLAB R2026a testing, validation, and CI workflow for matlab.unittest, MATLAB Test, Simulink Test, coverage, artifact generation, GitHub Actions, and open-source reproducibility. Use whenever MATLAB work needs verification, regression tests, CI, GitHub publication, or acceptance criteria.

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Writes professional bug bounty reports for HackerOne, Bugcrowd, and Intigriti with CVSS 4.0 scoring, business impact, working exploits, and remediation. Runs 5-check Pre-Report Verification first: hallucination detection, AI writing patterns, PoC reproducibility, duplicate detection, and impact plausibility. Use when user describes a vulnerability, shares HTTP logs, HAR files, recon output, or screenshots; says 'write a bug report', 'format my finding', 'draft a vuln report', 'is this valid', 'rate my vulnerability', 'verify my report', or any variant. Trigger for partial or messy input — raw notes, one-liners, or full writeups all work. Do not wait for perfect input.

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Apply source-aware mechanical-engineering judgment to research, analysis, coding, writing, teaching, research identity, and release work. Use for thermal-fluid systems, heat transfer, fluid mechanics, thermodynamics, HVAC, energy systems, turbomachinery, piping, multiphase flow, experiments, correlations, CFD, reduced-order models, AI/ML, uncertainty, engineering datasets, literature reviews, citations, manuscripts, reviewer revisions, Overleaf packages, figures, proposals, research software, reproducibility, public releases, engineering teaching materials, or a research-project logo and visual identity.

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Use when a task needs the judgment of a Computer and Information Research Scientist — designing an ablation to attribute an empirical gain, budgeting an NSF CISE proposal against page and content limits, deciding what reproducibility artifacts to release with a paper, screening a draft for mathiness or terminology misuse, or scoping the consent/ethics review needed before running an experiment on real users.

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Unity procedural generation design-to-code translation. Noise-based terrain/placement, tile & grid systems, dungeon/room generation, seed & reproducibility, content budget & constraint systems, runtime vs baked generation. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.

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Write and harden reusable agent-loop specification documents for biomechanics, data science, and vailá coding work. Use when the user says `/preto-loop`, asks to write/create/forge/specify/document an agent loop, turn an iterative vailá task into an autonomous loop, make an overnight loop, or design a biomechanics, data-pipeline, markerless-tracking, testing, refactoring, or performance loop. Include external verification, scientific validity, GUI/CLI parity, reproducibility, memory, guardrails, and named terminal states. Do not use merely to repeat a fixed scheduled prompt, execute an existing loop, or create unrelated documents.

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Find and work with ENCODE single-cell genomics data including scRNA-seq and scATAC-seq. Use when the user asks about single-cell experiments, cell type resolution, clustering from ENCODE data, deconvolution of bulk signals using single-cell references, or comparing single-cell vs bulk profiles. Covers platform differences (10X Chromium, Smart-seq2, Drop-seq), quality limitations of single-cell data, multimodal integration (RNA+ATAC), and cross-study reproducibility concerns. Also use for cell type annotation, gene detection limits, dropout artifacts, and single-cell data structure in ENCODE.

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Track exact provenance for every operation on ENCODE data — tool versions, reference files, scripts, parameters, and timestamps — to enable publication-ready methods writing. Use when the user processes ENCODE files, runs any bioinformatics tool, creates filtered/merged datasets, runs pipelines, performs liftover, uses R/Python/Bash for analysis, or needs to document their analysis chain for reproducibility and publication. Also use when the user says "write me methods" to auto-generate methods sections from the provenance log. This skill implements comprehensive provenance documentation: every tool, every version, every reference file, every parameter, every accession — no shortcuts. Use this skill for ANY processing step, ANY file transformation, ANY analysis operation on ENCODE data.

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Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

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Core statistical methodology and pedagogical approach for all Inquiro analyses. Always loaded to maintain teaching quality and reproducibility standards.

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Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.

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Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

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Maps between gene identifier systems (Ensembl, Entrez, HGNC symbol, UniProt, RefSeq, MANE) using AnnotationDbi, biomaRt, mygene, pyensembl, and Ensembl REST. Encodes Ensembl version stripping with GENCODE _PAR_Y preservation, the Ziemann 2016 Excel autocorrect debacle and Bruford 2020 HGNC renames (SEPT*->SEPTIN*, MARCH*->MARCHF*, MARC*->MTARC*, DEC1->DELEC1), OCT4/POU5F1 alias resolution, biomaRt archive endpoints for release pinning, the `filters` (plural) gotcha, MANE Select for clinical reporting, cross-species orthology via Ensembl Compara / OMA / OrthoDB, and tx2gene construction for tximport. Use when converting gene IDs across systems, handling renamed symbols, building tx2gene, pinning to a specific Ensembl release for reproducibility, or mapping cross-species orthologs.

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Performs differential expression on bulk RNA-seq count data with edgeR's negative-binomial GLM and quasi-likelihood F-test framework. Covers DGEList construction, filterByExpr, TMM/TMMwsp normalization, robust dispersion estimation, glmQLFit/glmQLFTest, TREAT for magnitude-bounded hypotheses, contrasts via no-intercept designs, voom and voomWithQualityWeights for heterogeneous samples, and the edgeR v4 bias-corrected APL changes. Use when running bulk DE with edgeR, choosing edgeR over DESeq2 (small n, transcript DE via catchSalmon, large samples), needing TREAT for a fold-change-threshold hypothesis, troubleshooting v3-to-v4 reproducibility, building paired or interaction designs, or handling library-quality heterogeneity.

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Comprehensive quality control for CLIP-seq libraries (eCLIP, iCLIP, iCLIP2, PAR-CLIP) covering library complexity (preseq), FRiP, IDR replicate reproducibility, read-distribution metagene, SMInput vs IgG control rationale, rRNA / snoRNA contamination, fragment-length distribution, and ENCODE-compliance thresholds. Use when assessing whether a CLIP library passed, deciding lenient vs stringent peak thresholds, comparing replicates with IDR rescue and self-consistency ratios, or distinguishing failed IP from over-amplified library.

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Queries myvariant.info BioThings aggregator for ClinVar, gnomAD, dbSNP, dbNSFP, COSMIC, CADD, and CIViC annotations in batched, version-tracked requests. Use when annotating variant lists from multiple databases simultaneously without managing per-source APIs, and when reproducibility-grade analyses require recording source data versions via _meta.

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