「agreement」の検索結果

Cross-method decision tree for calling hits in pooled CRISPR screens. Catalogs statistical models (MAGeCK RRA, MAGeCK MLE, BAGEL2, drugZ, JACKS, Chronos, CERES), experimental designs each is built for, failure modes outside design domain, reconciliation when methods disagree, multiple-testing and effect-size thresholds, the order of operations (count -> QC -> CN-correct -> hit-call -> validate), the second-best-sgRNA conservative rule, and consensus-hit strategy. Use when choosing among MAGeCK / BAGEL2 / drugZ / JACKS / Chronos for a given design, reconciling disagreement across two or three methods on the same screen, deciding whether to require consensus, gating downstream validation by hit-confidence tier, or interpreting unstable hit lists across reruns.

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。

Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.

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。

Map N6-methyladenosine (m6A) RNA modifications at single-nucleotide resolution using miCLIP (Linder 2015), miCLIP2 + m6Aboost machine learning (Kortel 2021), GLORI (Liu 2023, antibody-free chemical conversion), DART-seq (Meyer 2019, APOBEC1-YTH fusion), m6Anet (nanopore direct RNA), or MeRIP-seq with calibration. Use when distinguishing antibody-based from antibody-free m6A detection methods, applying the DRACH motif constraint, reconciling cross-method disagreements (DART 44% in DRACH vs GLORI), or detecting m6Am at the cap.

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。

Identifies differentially bound ChIP-seq regions between conditions using DiffBind, csaw (sliding windows), DESeq2/edgeR/PyDESeq2 on count matrices, NormR (control-aware), or MAnorm2. Distinguishes three distinct normalization problems (composition bias, trended bias, global shifts) and matches each to its appropriate fix including spike-in scaling. Use when comparing ChIP-seq binding between experimental conditions, choosing normalization for global vs local changes, integrating spike-in data, or reconciling DiffBind/DESeq2 disagreement.

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。

Use this skill when the user asks how to build + manage direct shipper relationships — moving from spot market to dedicated lanes, customer scoring + credit assessment, contract terms, dedicated capacity agreements, KPI reporting, and how to handle customer disputes. Reference standard customer-carrier contract terms.

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。

Use this skill when the user asks about getting/maintaining motor carrier operating authority — USDOT number, MC number, BOC-3 process agent, insurance filing (MCS-90, BMC-91/91X), Unified Carrier Registration (UCR), International Registration Plan (IRP), International Fuel Tax Agreement (IFTA), state-level permits (NY HUT, KY weight distance, OR weight-mile, NM weight distance), new entrant safety audit, intra vs interstate, for-hire vs private. Cite 49 CFR 365, 387, 390.

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。

Use this skill when the user asks about truck purchase financing, leasing options, factoring, fuel surcharge math, lease-purchase agreements, the total-cost-of-ownership (TCO) comparison between buying + leasing, and how owner-operators finance their first truck. Cover Section 179 + Bonus Depreciation tax treatment.

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。

Use this skill when the user asks about carrier-driver relationships — Independent Contractor (IC / 1099) vs Employee (W-2), Owner-Operator lease agreements, the AB5 California law, the DOL 2024 IC test, lease-purchase programs from the carrier side, settlement statements, deductions, and how to structure a compliant IC arrangement. Cite 49 CFR 376 + 1099 IRS rules.

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。

Use this skill when the user asks the difference between a freight broker, freight forwarder, and motor carrier (49 CFR 371 + 373) — required authority for each, bond requirements (BMC-84 broker bond, BMC-85 freight forwarder bond), broker-carrier agreements, factoring + commissions, double brokering, and how to identify each role on a Bill of Lading. Cite 49 CFR 371 + 373.

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。

Analyze development-set disagreements between human annotations and one Coval text LLM judge, then propose a focused prompt revision. Use coval-calibrate-metric for independent trust measurements.

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。

GitHub issue を起点に実装を始めるときに、実装より前に使うスキル。「issue

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

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。

Create employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.

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。

AI legal document generation powered by CellCog. Contracts, NDAs, terms of service, privacy policies, freelance agreements, employment contracts, compliance reviews, legal research. Precision legal drafting from natural language prompts. Not legal advice.

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。

Legal contract analysis using CUAD dataset (41 risk categories). Supports NDA, SaaS, M&A, employment, payment/merchant, and finder/broker agreements. Identifies red flags, suggests redlines, compares to market standards.

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。

Analyzes contracts and agreements for risks, unusual terms, and missing clauses

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。

中国合同审查工具。Use when user needs to review contracts, identify risks, check compliance, or get legal suggestions. Supports labor contracts, sales contracts, rental agreements, service contracts. 中国合同审查、合同风险分析、合同合规检查。

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。

Draft privacy policies, terms of service, disclaimers, and legal notices. Creates GDPR-compliant texts, cookie policies, and data processing agreements. Use PROACTIVELY for legal documentation, compliance texts, or regulatory requirements.

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。

Use when wiring shadcn/ui primitives, forms or admin UI in site-os — the component mechanics, the VBField validation layer, and the UI bugs that have actually shipped here. For brand identity (colour, type, logo, voice) load brand instead; that skill wins on any disagreement.

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。

Use when a high-stakes analysis, citation set, or decision should be checked by a second independent AI agent that verifies rather than decides, or when disagreement between agents must be surfaced for the human to adjudicate.

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。

Generate professional PDFs from Markdown using Pandoc and LaTeX with AI-powered content generation. Creates whitepapers, term sheets, memos, agreements, SAFEs, NDAs, and more.

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。

Analyzes contracts and agreements for risks, unusual terms, and missing clauses

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。

Model an organization with BDI-inspired perceptions, expressed goals, accommodations, and levels of agency. Use for socio-technical diagnosis where actors interpret the same situation differently and agreement is partial. NOT for individual AgentSpeak execution, normative conflict algorithms, or ordinary workflow diagrams.

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。