'strict' 검색 결과

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implements missing-data sensitivity analyses for confirmatory clinical trials including MMRM under MAR (with Kenward-Roger correction), reference-based multiple imputation (J2R, CR, CIR, LMCF per Carpenter-Roger 2013), Permutt delta-adjustment / tipping-point analysis, pattern-mixture identifying restrictions (CCMV, NCMV, ACMV), and the Cro vs Bartlett variance debate. Use when handling missing primary or secondary endpoint data in regulatory submissions following NRC 2010 and ICH E9(R1).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill, PWP, WLW), and interval-censored data. Use when analyzing time-to-event endpoints (OS, PFS, DOR, TTR, TTNT) in oncology or other clinical trials.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Strict SMILES validation, structural comparison, and modification verification. Catches invalid LLM-generated molecules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Extract parties, obligations, restrictions, permitted disclosures, and expiry dates from non-disclosure agreements.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Shakes your mental models with critical rigor, challenges assumptions, exposes blind spots, and provides multi-perspective insights as a strict thinking mentor. Deliberately breaks format conventions to stimulate genuine cognitive discomfort. Use when you want to stress-test an idea, shake your mental model, ask to challenge my assumptions, find blind spots, deepen my thinking, or request critical review with phrases like yusaburi or what do you think of this plan.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Transform review analysis into constructive feedback with actionable improvements. Mentor/shepherd mode - strict but supportive. Use for "give constructive feedback", "shepherd this paper". 旧名 review-shepherd。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze a paper draft objectively and strictly. Identifies logic gaps, missing proofs, structural issues, and research weaknesses. Reviewer mode. Use for "analyze this paper", "find weaknesses in draft". 旧名 review-analyze。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when building PHP applications with modern PHP 8.3+ features, Laravel, or Symfony frameworks. Invokes strict typing, PHPStan level 9, async patterns with Swoole, and PSR standards. Creates controllers, configures middleware, generates migrations, writes PHPUnit/Pest tests, defines typed DTOs and value objects, sets up dependency injection, and scaffolds REST/GraphQL APIs. Use when working with Eloquent, Doctrine, Composer, Psalm, ReactPHP, or any PHP API development.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generates strictly typed Drizzle ORM schemas for PostgreSQL with indexes, foreign keys, and Zod schema deduction.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generates, normalizes, and converts bedGraph signal tracks (4-column chrom/start/end/value, 0-based half-open) with bedtools genomecov, deepTools bamCoverage/bamCompare/bigwigCompare, bedtools unionbedg, and UCSC bedGraphToBigWig. Covers why a raw coverage bedGraph is not comparable across samples until normalized, the CPM/RPKM/BPM/RPGC normalization menu and the conserved-total assumption that makes them wrong under a global perturbation, the strict sorted-non-overlapping-chrom.sizes bedGraphToBigWig contract that silently corrupts a bigWig, effective-genome-size selection, and bin-size aliasing. Use when building or normalizing a coverage/signal track from a BAM, comparing tracks across samples or conditions, converting bedGraph to a browser-ready bigWig, or diagnosing a track that looks plausible but reports wrong heights.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Calls significant loops from protein-directed and targeted 3C assays (HiChIP, PLAC-seq, Capture Hi-C/PCHi-C, ChIA-PET) where the contact background is peak-anchored and coverage-biased, so generic Hi-C loop callers (cooltools dots, Juicer HiCCUPS) use the wrong null. Covers FitHiChIP (config-driven coverage+distance-decay spline regression, peak-to-peak vs peak-to-all foreground, loose vs stringent background, coverage vs ICE bias), MAPS (positive Poisson regression on bias factors for PLAC-seq/HiChIP), hichipper (restriction-site-distance bias model + library QC), CHiCAGO (Delaporte two-component Brownian+technical background for asymmetric bait x other-end Capture Hi-C), the with/without separate-ChIP anchor decision, and differential loops via diffloop. Use when calling loops from HiChIP/PLAC-seq/Capture Hi-C, choosing FitHiChIP/MAPS/CHiCAGO, picking peak-to-all vs peak-to-peak, setting the loop FDR, supplying ChIP peaks as anchors, QCing a HiChIP library, or comparing loops between conditions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill, PWP, WLW), and interval-censored data. Use when analyzing time-to-event endpoints (OS, PFS, DOR, TTR, TTNT) in oncology or other clinical trials.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implements missing-data sensitivity analyses for confirmatory clinical trials including MMRM under MAR (with Kenward-Roger correction), reference-based multiple imputation (J2R, CR, CIR, LMCF per Carpenter-Roger 2013), Permutt delta-adjustment / tipping-point analysis, pattern-mixture identifying restrictions (CCMV, NCMV, ACMV), and the Cro vs Bartlett variance debate. Use when handling missing primary or secondary endpoint data in regulatory submissions following NRC 2010 and ICH E9(R1).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when generating or modifying any Spring Boot class — controllers, services, repositories, DTOs, mappers, or configuration. Enforces strict layer separation and prevents business logic from leaking across boundaries.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Combine React's official "You Might Not Need an Effect" guidance with this project's stricter no direct useEffect stance. Use when writing, reviewing, or refactoring React components that might reach for useEffect, derived state, event relays, reset logic, subscriptions, or client fetching.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Genera tickets profesionales de soporte para Meta Business Suite / WhatsApp Business API optimizados para recibir prioridad URGENTE 24hr resolution. Úsala SIEMPRE que el usuario mencione crear un ticket a Meta, escalar un caso WABA, apelar un ban o restricción, reportar un false positive, abrir caso de soporte WhatsApp Business, problema de onboarding, rechazo de template, errores de Cloud API, OTP delivery, verification stuck, BM restricted, display name rejection, o cualquier issue de una WhatsApp Business Account. También activa cuando el usuario dice frases como "ayúdame a redactar un caso para Meta", "necesito reportar esto a soporte", "hay que escalar esto a WhatsApp", "ticket para Meta", o describe un problema de una cuenta de cliente de Vambe sin pedir ticket explícitamente pero claramente necesita uno. También activa ante preguntas del tipo "¿cómo apelar esto?" o "¿qué hago si Meta dice X?" relacionadas con WABA, BM o verificación.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

You are a senior backend engineer operating production-grade services under strict architectural and reliability constraints. Use when routes, controllers, services, repositories, express middleware, or prisma database access.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Migration guide for Swift and iOS. Use when migrating ObservableObject to @Observable (iOS 17), enabling Swift 6/6.2 Strict Concurrency, fixing @MainActor/Sendable warnings, adopting Approachable Concurrency (Swift 6.2), or handling iPadOS 26 windowing system changes (UIRequiresFullScreen deprecation). Covers breaking changes and version upgrade tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Establish and enforce coding standards, best practices, and architectural patterns across the codebase using linters, formatters, and code review processes. Use when setting up ESLint/Prettier, configuring linting rules, creating code style guides, implementing pre-commit hooks, establishing naming conventions, enforcing TypeScript strict mode, maintaining consistency, conducting architecture reviews, or defining team coding standards.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Enforces modern TypeScript best practices for type-safe code, strict configuration, runtime validation, and clear type contracts. Use when writing or reviewing TypeScript/JavaScript code, configuring tsconfig.json, or when the user asks for TypeScript style guidance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.