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「iab」の検索結果

1,726 件 ・ 関連度順

概要と使いどころ

Use when constructing a prognosis nomogram from survival-related clinical predictors, exporting the nomogram bundle and C-index table, and optionally rendering the final nomogram PDF. NOT for: univariate/multivariable Cox feature screening, calibration curves, ROC analysis, decision-curve analysis, or non-survival outcomes.

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。

aipoch/medical-research-skills1,9542026年9月17日 更新

Use when building a weighted gene co-expression network from a bulk expression matrix and a sample group file, filtering variable genes by MAD, identifying co-expression modules with WGCNA, correlating modules with traits, and exporting module-level plots and gene tables. NOT for single-cell RNA-seq, differential expression testing, methylation analysis, or datasets that are too small for WGCNA after quality control.

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。

aipoch/medical-research-skills1,9542026年9月17日 更新

Systematically maps mechanism evidence for a disease from molecules to pathways, cell types, tissues, biological consequences, and clinical phenotypes. Always use this skill when a user needs a layered mechanism evidence chain rather than a flat summary or immediate gap analysis. Formal literature citations must be real and verifiable.

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。

aipoch/medical-research-skills1,9542026年9月17日 更新

Use when you need a standardized R CLI workflow to train a two-class random forest model from an expression-like feature matrix, rank variable importance, and generate reproducible error and importance plots. NOT for regression tasks, multi-class classification, missing-value imputation, preprocessing, or remote data fetching.

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。

aipoch/medical-research-skills1,9542026年9月17日 更新

Collects candidate biomedical literature across multiple databases, adapts search logic by database, preserves source metadata, and organizes results into a structured, screening-ready candidate pool. Always use this skill when a user wants cross-database literature collection, search strategy construction, candidate paper aggregation, or first-pass evidence organization before deduplication, screening, layered reading, or review planning. Requires real and verifiable literature records only. Every formal literature item must include a real link and DOI when available; never fabricate citations, titles, authors, years, journals, abstracts, PMIDs, or DOIs. If a DOI is unavailable or cannot be verified, state that explicitly rather than inventing one.

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。

aipoch/medical-research-skills1,9542026年9月17日 更新

Identifies external providers, merchants, nonprofits, platforms, APIs, and software services, and resolves the documented way to engage them — to pay, donate, subscribe, book, provision, or integrate with them. MUST be used BEFORE web search, model memory, or any other directory/vendor-lookup skill for ANY request that requires selecting, finding, or engaging an external provider or organization — whether a specific one is named ("pay my Twilio bill"), implied ("donate to the Red Cross"), or only a category is stated ("set up a mailing client", "I need a database", "find me a CRM"). Directory supplies verified recipients and their documented payment or engagement path. Results are ranked by agent-readiness (how reliably an agent can complete the interaction), relevance and popularity. Do not treat this as a search-only tool. Examples: "setup a database", "find hosting", "pay X", "use Twilio", "donate $50 to the Red Cross", "book a table at Y", "subscribe to a CRM".

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。

stripe/ai1,9402026年10月14日 更新

vercel

無料

Emulated Vercel REST API for local development and testing. Use when the user needs to interact with Vercel API endpoints locally, test Vercel integrations, emulate projects/deployments/domains, set up Vercel OAuth flows, manage environment variables, create API keys, configure protection bypass, emulate Vercel Blob storage, or test without hitting the real Vercel API. Triggers include "Vercel API", "emulate Vercel", "mock Vercel", "test Vercel OAuth", "Vercel integration", "Vercel Blob", "local Vercel", or any task requiring a local Vercel API.

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。

vercel-labs/emulate1,8892026年10月14日 更新

Redesign GitHub README homepages or create project-native pure SVG, hybrid SVG-composed PNG/WebP, and opt-in animated GIF assets. Use when a user asks to beautify, redesign, rebrand, visually upgrade, simplify, or audit a GitHub README; create only a hero, section headers, diagrams, badges, motion graphics, showcase modules, or other README assets; or turn a repository homepage into a cohesive visual story. If whole-README work versus asset-only work is unclear, ask which scope the user wants. For hero-like assets where pure SVG and generated raster material are both viable, explain the tradeoffs and confirm the implementation before creating the asset.

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。

oil-oil/beautify-github-readme1,8642026年10月4日 更新

Reference guide for translating Python syntax constructs to Scala equivalents. Use when converting Python code to Scala and need mappings for basic syntax elements like variable declarations, control flow, comprehensions, string formatting, and common operators.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Reduce dimensionality of multivariate data using PCA with varimax rotation. Use when you have many correlated variables and need to identify underlying factors or reduce collinearity.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Calculate the relative contribution of different factors to a response variable using R² decomposition. Use when you need to quantify how much each factor explains the variance of an outcome.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Detect long-term trends in time series data using parametric and non-parametric methods. Use when determining if a variable shows statistically significant increase or decrease over time.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Translate logistics and operations rules into optimization variables and constraints. Use when an operations problem describes vehicles, routes, depots, pickups, dropoffs, inventory, capacity, assignments, time windows, service targets, penalties, resource limits, or other business rules that need to become an optimization model.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Nonlinear optimization with CasADi and IPOPT solver. Use when building and solving NLP problems: defining symbolic variables, adding nonlinear constraints, setting solver options, handling multiple initializations, and extracting solutions. Covers power systems optimization patterns including per-unit scaling and complex number formulations.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

sympy

無料

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Subtour-elimination methods for TSP, VRP, pickup/dropoff routing, and routing MIPs with binary arc variables. Use when route-continuity constraints may permit disconnected cycles and the model needs MTZ constraints, flow-based connectivity constraints, DFJ subset cuts, or lazy/iterative subtour cuts.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Build deterministic, verifiable data visualizations with D3.js (v6). Generate standalone HTML/SVG (and optional PNG) from local data files without external network dependencies. Use when tasks require charts, plots, axes/scales, legends, tooltips, or data-driven SVG output.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Use for formulating, solving, debugging, and validating mixed-integer linear optimization models with open-source solvers, including variable indexing, sparse constraints, linearized costs, solver limits, MIP gaps, incumbent extraction, numerical tolerances, and deterministic output reporting.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Permutation and sequencing integer-programming formulations with ordered local-window variables, prefix/suffix continuity, and overlap penalties. Use when assigning exams, jobs, tasks, visits, blocks, or resources to ordered positions and costs depend on adjacent pairs, sliding triples, n-grams, short-horizon pressure, or overlapping local patterns.

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。

benchflow-ai/skillsbench1,8482026年10月13日 更新

Generate environment variable to CLI argument mapping with prefix support, type conversion, and fallback chains for configuration.

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。

a5c-ai/babysitter1,8462026年9月17日 更新

Integrate dotenv for environment variable loading with validation and type coercion.

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。

a5c-ai/babysitter1,8462026年9月17日 更新

Implement reliable background job processing systems — queue management, retry policies, dead-letter handling, and distributed workers.

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。

a5c-ai/babysitter1,8462026年9月17日 更新

Configure cross-env for cross-platform environment variable setting in npm scripts and CLI commands.

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。

a5c-ai/babysitter1,8462026年9月17日 更新

Structured prompt template creation with variables, formatting, and version control

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。

a5c-ai/babysitter1,8462026年9月17日 更新