「quant」の検索結果

Performs zero-shot time-series forecasting with Google's TimesFM, including regular-grid CSV preparation, quantile forecasts, XReg covariates, and held-out evaluation. Uses the Apache-licensed TimesFM 2.5 checkpoint by default and documents the distinct TimesFM 3.0 multivariate API and weight-license 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。

Supports local computational pathology research with PathML: slide loading and tiling, preprocessing and QC, h5path storage, multiplex quantification, spatial graphs, and bounded model inference. Use for whole-slide H&E, CODEX, Vectra, Mesmer, HoVer-Net, and HACTNet workflows.

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。

Processes mass spectrometry data with pyOpenMS. Supports proteomics and metabolomics workflows—feature detection, peptide/protein identification, label-free quantification, adduct/accurate-mass annotation, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. For simple spectral comparison and small-molecule library matching use matchms.

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。

Writes scientific Markdown documentation and Mermaid diagrams for workflows, relationships, timelines, and schemas. Provides syntax references, document templates, accessibility guidance, and version-aware rendering checks. Use when a user requests Markdown, Mermaid, or a text-based structural diagram; quantitative scientific figures require suitable plotting tools.

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。

Plans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.

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。

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

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。

Looks up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), scores variants or scans windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and builds Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.

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 cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.

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。

Snapshot of a single wallet's token holdings on a specific chain — list of every token currently held with name, symbol, current price, 24h price change, and holding quantity. Use when the user provides an explicit wallet address (or says "my wallet") and wants the current portfolio: "what does 0x... hold", "wallet balance breakdown", "list positions for this address", "what tokens are in this wallet", "show me the holdings of <address>".

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。

Turns resume duties into truthful impact bullets. Questions the user role by role to dig out achievements, asks for real numbers or honest ranges (never invents them), and writes concise bullets in XYZ, CAR, scope or qualitative form. Use when the user says "rewrite my bullets", "make this bullet stronger", "quantify my resume", "turn my duties into achievements", "improve my experience section", "my resume sounds boring", "I don't have any numbers", pastes resume lines for feedback, or works in a low-number job (nursing, teaching, care, trades, admin, creative). With the Reactive Resume MCP server connected, it edits experience, project, volunteer and education descriptions with apply_resume_patch after the user approves. Use resume-content-guide instead for which sections or details belong and for summaries or headlines, resume-tailor to fit one job posting, interview-prep or mock-interview for interview stories and practice, and resume-builder to build a resume from scratch.

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。

Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastructure.

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 an outage, production incident, or significant service degradation has occurred and the team needs to write a structured blameless post-mortem. Triggers on phrases like "write a post-mortem", "incident review", "what went wrong", "outage report", "root cause analysis", or "RCA". Covers timeline reconstruction, contributing factor analysis, impact quantification, and action item generation with owners.

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。

Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel.

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。

Systematic stock screening and investment idea sourcing. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Use when looking for new ideas, running screens, or conducting thematic sweeps. Triggers on "idea generation", "stock screen", "find ideas", "what looks interesting", "screen for", "new ideas", or "pitch me something".

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, modify, and optimize quantitative trading strategies, then backtest and evaluate them.

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。

Geopolitical risk analysis: quantify crisis signals, identify precursors, and build event-driven strategies for war, sanctions, and supply disruption scenarios.

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。

Behavioral finance applications: theories of overreaction and underreaction, behavioral explanations for momentum and reversal, investor sentiment cycles, cognitive-bias checklists, and debiasing quantitative strategies.

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。

Factor research framework with IC/IR analysis, quantile backtesting, and factor combination. Suitable for cross-sectional factor evaluation across multiple instruments.

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。

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

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。

Works out what to reorder and when, from what is actually selling: pulls sales history and stock on hand from Shopify, Square, NetSuite, or an uploaded CSV, computes 7-day and 28-day sales velocity per item, projects a conservative stockout date for each, sizes a 60-day reorder quantity, and drafts the purchase orders and vendor emails to cover it. Flags the money sitting still too — overstock, dead stock, and zero-velocity items, reported as slow movers to clear rather than things to buy more of. Seasonality is applied where the history supports it and named where it does not. Nothing is ordered and no vendor is emailed without approval. Reach for this whenever stock comes up — "what do I need to reorder," "am I going to run out," "what should I order this month," "we keep running out of filters," "how much cash is sitting in the warehouse," "what is not moving," or "draft a PO for my supplier."

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。

Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-fact log analysis; not a hosted notary; not a legal opinion.

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。

Senior Project Manager for enterprise software, SaaS, and digital transformation projects. Specializes in portfolio management, quantitative risk analysis, resource optimization, stakeholder alignment, and executive reporting. Uses advanced methodologies including EMV analysis, Monte Carlo simulation, WSJF prioritization, and multi-dimensional health scoring. Use when a user needs help with project plans, project status reports, risk assessments, resource allocation, project roadmaps, milestone tracking, team capacity planning, portfolio health reviews, program management, or executive-level project reporting — especially for enterprise-scale initiatives with multiple workstreams, complex dependencies, or multi-million dollar budgets.

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 reviewing a specific inbound deal before close — when sales has asked for a discount that exceeds AE authority, when the customer has redlined the MSA, when per-deal economics (margin after discount, multi-year payment shape, indemnity exposure) need to be quantified, or when discount approval needs to be routed to a named human approver (Sales Director, VP Sales, CFO, CRO, General Counsel). Covers deal review, discount approval routing, per-deal margin scoring, deal exception handling, MSA redline triage, contract landmine detection (uncapped indemnity, MFN, perpetual license-back, missing DPA), and named-approver chain assembly. NEVER auto-approves — every output is a numeric scorecard plus a routing recommendation to a named human.

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。

Security leadership for growth-stage companies. Risk quantification in dollars, compliance roadmap (SOC 2/ISO 27001/HIPAA/GDPR), security architecture strategy, incident response leadership, and board-level security reporting. Use when building security programs, justifying security budget, selecting compliance frameworks, managing incidents, assessing vendor risk, or when user mentions CISO, security strategy, compliance roadmap, zero trust, or board security 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。