1,440 件 ・ 関連度順
概要と使いどころ
Model interpretability via SHAP (Shapley values from game theory). Covers explainer choice (Tree, Deep, Linear, Kernel, Gradient, Permutation), feature attribution, and plots (waterfall, beeswarm, bar, scatter, force, heatmap). Use to explain ML predictions, rank features, debug models, audit fairness, or compare models. Works with tree, deep, linear, and black-box models.
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。
Per-feature NaN-safe Spearman/Pearson correlation across many features (genes, proteins, variants) with missing values. Covers why bulk matrix shortcuts fail, correct pairwise deletion, degenerate input filtering, and large-dataset performance. Use statistical-analysis for test choice; shap-model-explainability for interpretability.
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。
Guidelines for clinical decision support (CDS) documents: biomarker-stratified cohort analyses and GRADE-graded treatment reports. Covers structure, executive summaries, evidence grading (1A–2C), stats (HR, CI, survival), and biomarker integration. Use for pharma research docs, clinical guidelines, regulatory submissions.
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。
15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
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。
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
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。
AWS cost optimization, monitoring, and operational excellence expert. Use when analyzing AWS bills, estimating costs, setting up CloudWatch alarms, querying logs, auditing CloudTrail activity, or assessing security posture. Essential when user mentions AWS costs, spending, billing, budget, pricing, CloudWatch, observability, monitoring, alerting, CloudTrail, audit, or wants to optimize AWS infrastructure costs and operational efficiency.
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。
Provides AWS Lambda integration patterns for PHP with Symfony using the Bref framework. Creates Lambda handler classes, configures runtime layers, sets up SQS/SNS event triggers, implements warm-up strategies, and optimizes cold starts. Use when deploying PHP/Symfony applications to AWS Lambda, configuring API Gateway integration, implementing serverless PHP applications, or optimizing Lambda performance with Bref. Triggers include "create lambda php", "deploy symfony lambda", "bref lambda aws", "php lambda cold start", "aws lambda php performance", "symfony serverless", "php serverless framework".
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。
When the user wants to write an email to an investor — cold outreach, warm intro request, follow-up after a meeting, monthly investor update, or thank-you note. Also activates for "intro email", "investor email", "follow up with VC", or "investor update".
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。
Design sport-specific practice sessions. Drills by skill level and time, warm-up, skill work, scrimmage, cool-down.
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。
Build targeted prospect lists by analyzing LinkedIn profiles, extracting job titles, companies, locations, and recent activity. Identifies decision-makers, tracks job changes for warm outreach, and enriches contact data. Use when users need to find prospects, build lead lists, or track decision-maker movements.
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。
Drop a folder of vendor quotes, proposals, and SOWs on Cowork -- normalizes them into one comparison matrix, computes true total cost of ownership, surfaces the terms each vendor buried, and arms you with negotiation leverage points and reference-check questions.
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 applying a published cohort study's methodology to a different database. Extracts the design from the source paper, maps variables to the target database with a harmonization table, generates the analysis code and reports every forced deviation.
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 designing a study that benchmarks AI systems against a human-expert panel, before data collection. Plans the arms, decoupled rubrics with anchors, planted calibration probes, reviewer panel, inter-rater reliability targets and LLM-as-judge versus human adjudication.
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 comparing an exposure-outcome association across countries with parallel national surveys (KNHANES, NHANES, CHNS). Harmonizes variables, runs parallel weighted analyses and builds comparison tables for 2-country (KR+US) or 3-country (KR+US+CN) designs.
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。
Read remaining Claude Code and Codex subscription quota without spending it. Use when the user asks or after a vendor rejects work for quota; a caller such as rotate-agent may also arm a scheduled read on purpose. Never poll on your own; after a `wait` verdict, pass the reset wait to `sno heartbeat` and re-read once when it ends.
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。
Quota-triggered failover from Claude Code, Codex, Cursor, Hermes or OpenClaw. When armed, it reads the sender quota and tries other-vendor models in place, then receiving agents in the configured order. Use when a long run must finish even if one vendor's quota runs out. Not a monitor for anything else.
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。
Turn developer love into revenue by enabling champions and choosing a GTM model. Use when developers adopt the free tier but nobody pays, when the user is cold-selling the VP instead of arming the developer, or when picking between open-source, PLG, inbound, and sales-led.
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。
Harmonises data classification across jurisdictions mapping GDPR special categories vs CCPA sensitive PI (1798.140(ae)) vs HIPAA PHI (160.103) vs LGPD sensitive data (Art. 5-II). Provides cross-regulation mapping matrix for multinational compliance. Keywords: cross-jurisdiction, GDPR, CCPA, HIPAA, LGPD, sensitive data, multinational, classification mapping.
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。
AWS cost optimization, monitoring, and operational excellence expert. Use when analyzing AWS bills, estimating costs, setting up CloudWatch alarms, querying logs, auditing CloudTrail activity, or assessing security posture.
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。
Email infrastructure for AI agents. Create accounts, send/receive emails, manage webhooks, and check karma balance via the AgentMail 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。
Run structured AI red team exercises for jailbreak resistance, data exfiltration risk, harmful output controls, and agent tool abuse resilience.
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。
Production rigging in Blender with armatures, IK/FK, constraints, weight painting, mechanical rigs, facial rigs, and drivers. Use before animation on deforming assets via MCP.
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。
Stylized art direction for Blender with shape language, exaggeration, color harmony, NPR rendering, and hand-painted asset workflows. Use for non-photorealistic game and animation projects.
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。
Garment blockout, cloth simulation, pin groups, and bake to shape keys or caches for characters and props in Blender via MCP.
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。