「frame」の検索結果

Detect positive (diversifying / episodic / pervasive) selection using codon dN/dS frameworks. Implements PAML codeml site models (M0/M1a/M2a/M7/M8/M8a), branch models, branch-site model A (Zhang 2005), and HyPhy methods (BUSTED, BUSTED-S, BUSTED-MH, BUSTED-PH, MEME, FEL, FUBAR, aBSREL, SLAC, RELAX, GARD, FUBAR-MH). Includes McDonald-Kreitman framework (asymptotic alpha, impMKT, polyDFE, DFE-alpha, GRAPES) for within-species + divergence inference, RERconverge for trait-correlated rate shifts, CSUBST for convergent substitution, and PhyloAcc for accelerated noncoding evolution. Use when testing adaptive evolution at codons, branches, or full gene; running GARD recombination pre-screen; controlling alignment-error and gBGC false positives; reconciling PAML vs HyPhy results; or performing genome-scale selection scans.

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Applies ACMG/AMP 2015 framework with ClinGen SVI specifications, Tavtigian 2018/2020 Bayesian point system, Abou Tayoun 2018 PVS1 decision tree, Pejaver 2022 and Bergquist 2025 calibrated PP3/BP4 thresholds for REVEL/BayesDel/AlphaMissense, Brnich 2020 PS3/BS3 OddsPath, Walker 2023 SpliceAI splicing framework, and AMP/ASCO/CAP 2017 tumor tiers. Use when classifying germline variants P / LP / VUS / LB / B, applying VCEP-specific CSpec rules, computing Whiffin BS1, or assigning cancer Tier I-IV per Li 2017.

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Read, create, update, and pick contacts using the Contacts and ContactsUI frameworks. Use when fetching contact data, saving new contacts, wrapping CNContactPickerViewController in SwiftUI, handling contact permissions, or working with CNContactStore fetch and save requests.

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Tokenize, tag, and analyze natural language text using Apple's NaturalLanguage framework and translate between languages with the Translation framework. Use when adding language identification, sentiment analysis, named entity recognition, part-of-speech tagging, text embeddings, or in-app translation to iOS/macOS/visionOS apps.

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Trigger when: (1) User mentions "manimgl" or "ManimGL" or "3b1b manim", (2) Code contains `from manimlib import *`, (3) User runs `manimgl` CLI commands, (4) Working with InteractiveScene, self.frame, self.embed(), ShowCreation(), or ManimGL-specific patterns. Best practices for ManimGL (Grant Sanderson's 3Blue1Brown version) - OpenGL-based animation engine with interactive development. Covers InteractiveScene, Tex with t2c, camera frame control, interactive mode (-se flag), 3D rendering, and checkpoint_paste() workflow. NOT for Manim Community Edition (which uses `manim` imports and `manim` CLI).

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Use this skill when conditioning, loading, preparing, or labeling signal data for analysis or ML training. Covers: cleaning a single signal (fill gaps, remove drift, deoutlier, denoise, resample/align a time base) BEFORE analysis; building a `signalDatastore` pipeline; creating a `labeledSignalSet` for Signal Labeler; deriving labels (filename, folder, in-file, ROI, time-frequency ROI); stratified train/val/test splits; framing long signals; parallel processing; and shaping datastore output for `trainnet`. Triggers include "clean up this signal", "remove drift / detrend", "fill gaps", "remove spikes / outliers", "denoise", "resample to a uniform rate", "align channels", "labels from filenames", "stratified split", "prepare for Signal Labeler", and function names like `fillgaps`, `fillmissing`, `detrend`, `filloutliers`, `smoothdata`, `resample`, `synchronize`, `signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`.

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Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a vibration / biosignal / radar / sensor signal needing features for downstream ML or analysis. Includes optional GPU acceleration via canUseGPU and gpuArray. Does not cover filter design, audio-specific feature extraction (use audioFeatureExtractor in Audio Toolbox instead), batch dataset orchestration, or 2D / image features.

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Connect to and acquire images from cameras in MATLAB using Image Acquisition Toolbox. Use this skill when the user wants to: use a webcam, acquire images, capture video, stream from a camera, connect to a GigE Vision camera, preview live video, list available cameras, configure camera properties, use a CoaXPress frame grabber, or use a Camera Link frame grabber. Covers USB webcams, GigE Vision, USB3 Vision, CoaXPress, Camera Link, and GenICam-compliant cameras. Always prefer videoinput from Image Acquisition Toolbox over webcam support package or gigecam.

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Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload pipelines.

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When the user wants to plan growth using the AARRR framework, diagnose growth bottlenecks, or map actions across the customer lifecycle. Also use when the user mentions "growth funnel," "AARRR," "pirate metrics," "acquisition activation retention," "customer lifecycle metrics," or "growth framework." For retention tactics, use retention-strategy.

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Use when an agent drives Unity 6.3 (6000.3) on a Mac for any task: batch mode and -executeMethod jobs, a running editor (the user's GUI editor or a headless one), the Unity CLI and com.unity.pipeline, MCP servers, the Test Framework, command-line builds; when a batch run fails silently, 'Scripts have compiler errors', a capture comes back black or pink, or a result must be proven with numbers and a frame; or when a Unity brief must go to the right scenario-unity-* specialist.

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Use when a Unity 6.3 game is slow or stutters: low fps, frame spikes, hitches when entering areas or on first effects, GC spikes, too many draw calls or SetPass calls, CPU vs GPU bound questions, Profiler, Profile Analyzer, Memory Profiler, Frame Debugger or Project Auditor work, GPU Resident Drawer or SRP Batcher setup, LOD and Mesh LOD, shader warm-up and variants, memory or VRAM budgets, IL2CPP and build size, or proving a fix with numbers from a player.

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Use when making a trailer, cutscene, cinematic or short film in Unreal Engine 5.8 with Sequencer: shot lists, master and shot sequences, cameras, lenses, depth of field, camera cuts, spawnables, character animation in shots, per-shot lighting, Movie Render Graph or Movie Render Queue EXR renders, "render darker than the viewport", "first frames pop", "last frame missing", ACES or OCIO to DaVinci Resolve, the 180-degree rule, Sequencer Python, or reviewing a cut.

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Use when generating or extending video with Google Veo models on Scenario via MCP: text-to-video, image-to-video from a first frame, first and last frame transitions, reference-to-video (R2V) with asset or style reference images, native audio with dialogue, sound effects, and ambience, negative prompts, seeded reruns, extending a 16:9 clip, or choosing a quality, fast, or lite tier. Keywords: Veo 3.1, Veo 3.1 Fast, Veo 3.1 Lite, Extend Video, Google, T2V, I2V, V2V, 720p, 1080p.

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Use when generating video with Vidu models on Scenario via MCP: text-to-video, image-to-video from a single still, start and end frame interpolation, reference-to-video keeping characters and props consistent from up to 7 reference images or reference videos, anime-style motion, movement amplitude control, or deciding between Q3, Q2, Q1, and 2.0 tiers. Keywords: Vidu Q3 Pro, Q2 Turbo, Shengshu Technology, T2V, I2V, R2V, Reference2V, start end frame, background music toggle.

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Use when generating or editing video with Seedance models on Scenario via MCP: text-to-video, image-to-video, first and last frame anchors, reference-to-video from identity, product, or world references, prompt-based editing, extending a clip, audio-conditioned motion or voice, shot sound without music, first-frame versus reference conditioning, or an output blocked by moderation. Keywords: Seedance 2.5 and 2.0, ByteDance, T2V, I2V, V2V, native audio, OutputVideoSensitiveContentDetected.

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Use when generating, extending, or editing video with Gemini Omni models on Scenario via MCP: text-to-video, image-to-video from a first frame, reference-to-video keeping a character, product, or place consistent, appending footage to a clip, restyling footage by prompt (season, wardrobe, art style), native audio with dialogue and ambience, or picking between first-frame and reference conditioning. Keywords: Gemini Omni Flash, 1.1 Flash, Google, T2V, I2V, V2V, extend, subject consistency.

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Use when one approved visual, image or video, must ship at many sizes or placements through Scenario: adapting a master to 1:1, 4:5, 9:16, or 16:9, social formats for feeds and stories, YouTube thumbnails, storefront capsules and app store graphics, marketplace product images, link previews, display banners, a website hero, or choosing between crop, resize, expand, and generative reframe. Keywords: aspect ratio, resize, reframe, outpaint, expand, derivative, safe zone, thumbnail, banner.

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Design measurement frameworks including event taxonomy, KPI hierarchy, dashboard architecture, attribution models, and analytics implementation strategy. Use this skill whenever the user wants to plan analytics, design dashboards, build event taxonomies, define KPIs, set up tracking, or audit existing measurement. Triggers on analytics strategy, measurement plan, event taxonomy, tracking plan, KPI framework, dashboard design, north star metric, attribution model, conversion tracking, GA4 setup, Mixpanel setup, analytics audit. Also triggers when the user has data but no clear way to use it, or wants to make decisions but doesn't know what to track.

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Expert New Zealand Information Security Manual (NZISM) advisor for NZ government agencies and their supply chains. Use for NZISM control guidance, gap analysis, agency security obligations, classification framework (Unclassified through Top Secret), security risk management, system certification, and GCSB/NCSC NZ compliance. Triggers on: NZISM controls, NZ government security, GCSB compliance, agency cybersecurity obligations, NZ classification markings, Restricted/Confidential/Secret system scoping, agency security policies, third-party supplier security, Certification and Accreditation (C&A), and any question about NZ government information security requirements or the NZISM framework.

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Expert agile coaching: framework selection, maturity assessment, retrospective facilitation, transformation roadmaps. Use when selecting an agile framework, coaching teams, facilitating retrospectives, or designing a transformation.

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NIST Cybersecurity Framework 2.0 implementation, assessment, and compliance management. Use for CSF 2.0 gap analysis, cybersecurity risk management, maturity assessment, CSF profiles, and cross-framework compliance mapping.

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Evaluate and compare technology stacks with TCO analysis, security assessment, and ecosystem health scoring. Use when comparing frameworks, calculating total cost of ownership, assessing migration paths, or analyzing ecosystem viability.

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Brand strategy covering positioning, identity, brand architecture, messaging frameworks, and governance. Use when developing brand positioning, creating messaging frameworks, auditing brand health, or building brand architecture.

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。