'density' 검색 결과

Shared density-resolution contract for wave skills. Canonical detail on the D12 cascade, density resolver call, ad-hoc override workflow, and DocumentationDensityEvent telemetry emission. Referenced from nw-discover / nw-discuss / nw-design / nw-devops / nw-distill / nw-deliver.

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This skill recommends lifelong biochemical testing for recurrence in all patients with Cushing's syndrome after adrenalectomy, except those with resected adrenal adenoma showing CT density <10 Hounsfield units. Use when determining long‑term follow‑up strategy for a post‑adrenalectomy CS patient; triggers include “post‑adrenalectomy Cushing’s syndrome”, “CT density <10 HU”, and “adrenal adenoma resection”.

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This skill suggests follow-up tests for specific comorbidities associated with Cushing's syndrome in patients with adrenal adenoma when CT density is less than 10 Hounsfield units. Use when managing a post-adrenalectomy Cushing's syndrome patient with confirmed adrenal adenoma pathology and low-density imaging (<10 HU).

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This skill guides evaluation for malignancy using imaging in patients with a history of adrenal adenoma (post‑adrenalectomy Cushing’s syndrome) when the adenoma demonstrates a CT density of ≥10 Hounsfield units or when pathology is consistent with possible carcinoma. Trigger phrases include “CT density ≥10 HU”, “possible carcinoma on pathology”, and “post‑adrenalectomy CS patient with adrenal adenoma history”.

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Review website images for high-density displays, where standard assets can look blurry. Check higher-resolution versions, HTML and CSS image selection, delivery settings, and loading behavior, then identify specific files or components that need changes.

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• Investigating blurry images on high-density displays
• Reviewing srcset for fixed-size and responsive images
• Checking high-resolution CSS background images

Build falling leaves or petals with visible front-and-back tumbling and sideways motion tied to rotation. Covers 2D canvas and 3D implementations, depth layers, particle density, rendering costs, and reduced-motion support.

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• Add autumn leaves to a web page
• Animate drifting cherry blossom petals
• Create layered foliage in a 3D scene

Build a globe-like 3D visual in Three.js, a library for browser graphics. Combine a dense sphere of glowing particles with a thin orbital ring, then adjust color, density, tilt, and gentle motion.

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• Adding a planetary particle visual to a website
• Creating a data-globe effect for an infrastructure service
• Matching orbital ring colors to a brand

Build subtle animated petals, snow, confetti, or other decorative particles within a single page section. Adjust their movement and density while preserving readable content, limiting device workload, and providing static alternatives for readers who reduce motion.

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• Adding gentle petals or snow to a page section
• Animating small brand fragments behind content
• Limiting decorative animation on mobile devices

Create a dark animated backdrop with soft vertical folds of light, layered glow, and a brighter corner or lower edge. Adjust color, density, softness, and drift to build depth while keeping foreground content visually prominent.

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• Adding slowly drifting light curtains to a dark background
• Matching background glow to a brand accent color
• Concentrating light near a corner or lower edge

Make 3D canvas output sharper on Retina and other high-density displays. Coordinate rendering and post-processing resolution, preserve pointer accuracy, and verify fixed 200% rendering or automatic scaling with measured performance and explicit fallbacks.

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• Fix blurry 3D canvas output on Retina displays
• Implement a fixed 200% rendering option
• Keep post-processing and pointer coordinates aligned

Critique a rendered screen's density — cognitive load, content prioritisation, scanning patterns, and progressive disclosure. Use when a screen feels overwhelming. For the underlying choice-count principle, use `hicks-law` (interaction-design).

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Analyze spatial cell-cell interactions, neighborhoods, and niches in IMC/MIBI data with squidpy and imcRtools, covering neighborhood-enrichment permutation nulls, the abundance-vs-density confound, inhomogeneous Ripley's K, cellular-neighborhood discovery, graph-construction (contact vs proximity), and edge effects. Use when testing whether cell types co-locate, choosing a spatial null, building a neighbor graph, discovering tissue niches, or deciding whether a spatial pattern is real or a density/segmentation artifact.

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When the user wants to optimize content for SEO—word count, H2 keywords, keyword density, multimedia, tables, lists. Also use when the user mentions "content length," "word count," "keyword stuffing," "H2 keywords," "keyword density," "tables," "bullet points," or "content structure." For keywords, use keyword-research.

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Audit PowerPoint (.pptx) decks for slide count, text density, embedded images and fonts, hidden slides, speaker notes, and animation density. Use when reviewing a board deck, sales deck, or conference talk before sending.

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Create original short videos using the 时尚密度复位｜身份锁定、拼贴回顾与英雄主标 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants identity-locked style modules, a deliberate density reset, a recap collage, and a final hero lockup with new subjects and surfaces.

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Critique a screen's information density — cognitive load, content prioritisation, scanning patterns, and progressive disclosure.

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Match information density to platform and user type. Use when designing data tables, dashboards or toolbars, or adapting a desktop product for mobile.

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Use before generating, editing, or reviewing any user interface — a dashboard panel, a landing page, an email, a slide, an app screen. Sets three deliberate design dials (variance, motion, density) BEFORE generation so the output has a point of view instead of defaulting to the timid, uniform look that reads as "AI made this". Applies to Genesis's OWN dashboard UI, not only things built for others.

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因果推論・効果検証（A/B テスト / ABテスト / オンライン実験 / リフト / SRM / CUPED、観察データの処置効果 / ATE / ATT / CATE / 傾向スコア / propensity score / IPW / 二重頑健 / DML / causal forest、準実験 / 差の差 / DiD / イベントスタディ / 操作変数 / IV / 2SLS / 回帰不連続 / RDD / 合成コントロール）を実行したら必ずセットで出す図と値のルーター。 proportions_ztest, chisquare, statsmodels.stats.power, dowhy, econml, causalml, doubleml, propensity, LinearDML, IV2SLS, rdrobust, rddensity, pysyncon, treat*post がコードに現れたとき、またはユーザーが「ABテストの結果を 見て」「施策の効果を推定して」「差の差で」「傾向スコアで揃えて」「閾値前後で比較して」と言ったときに使う。SRM・ バランス・並行トレンド・first-stage に言及がなくても適用する。SKILL.md のルーティング表で設計を特定し、対応する references/<設計>.md を読んでから実行する。実験でない群間比較の検定は statistical-inference-diagnostics、 予測モデルの解釈（SHAP 等）は predictive-modeling-diagnostics を使う。

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Audit or design generative AI interfaces against three diagnostic pillars (deterministic-stochastic balance, interaction density, visual cohesion). Treats taste as a measurable control system, not subjective preference. Use when: 'taste audit', 'score this UI', 'design quality', 'interaction density', 'visual cohesion', 'refiner layer', 'correction cost', 'why does this feel off', 'polish this', 'design review', or building any user-facing AI product.

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Use when running an autonomous multi-hour build of a green-field product — orchestrates planner → contract → generator ⇄ evaluator loop with adaptive scaffolding density per model tier. Triggers on /mk:autobuild, "build me a kanban app", "build a retro game maker", "autonomous build", or any green-field product spec. NOT for scoped single-task work (see mk:cook); NOT for initial project scaffolding only (see mk:bootstrap).

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Produce variants of an existing Style by shifting tone (light/dark), density (compact/relaxed), or accent (palette rotation) while preserving the brand identity. Use when the user wants alternate themes derived from one brand.

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Analyze spatial cell-cell interactions, neighborhoods, and niches in IMC/MIBI data with squidpy and imcRtools, covering neighborhood-enrichment permutation nulls, the abundance-vs-density confound, inhomogeneous Ripley's K, cellular-neighborhood discovery, graph-construction (contact vs proximity), and edge effects. Use when testing whether cell types co-locate, choosing a spatial null, building a neighbor graph, discovering tissue niches, or deciding whether a spatial pattern is real or a density/segmentation artifact.

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Analyze spatial cell-cell interactions, neighborhoods, and niches in IMC/MIBI data with squidpy and imcRtools, covering neighborhood-enrichment permutation nulls, the abundance-vs-density confound, inhomogeneous Ripley's K, cellular-neighborhood discovery, graph-construction (contact vs proximity), and edge effects. Use when testing whether cell types co-locate, choosing a spatial null, building a neighbor graph, discovering tissue niches, or deciding whether a spatial pattern is real or a density/segmentation artifact.

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