「calibration」の検索結果

Turn reflection into decisions by scoring predictions against outcomes and tracking whether commitments held. Use when running a quarterly review, scoring forecast calibration, or reflection keeps producing notes instead of change.

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Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.

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Comprehensive best practices for robot perception systems covering cameras, LiDARs, depth sensors, IMUs, and multi-sensor setups. Use this skill when working with RGB image processing, depth maps, point clouds, sensor calibration (intrinsic, extrinsic, hand-eye), object detection, semantic segmentation, 3D reconstruction, visual servoing, or perception pipeline optimization. Trigger whenever the user mentions OpenCV, Open3D, PCL, RealSense, ZED, OAK-D, camera calibration, AprilTags, ArUco markers, stereo vision, RGBD, point cloud filtering, ICP registration, coordinate transforms, camera intrinsics, distortion correction, image undistortion, sensor streaming, frame synchronization, or any computer vision task in a robotics context. Also covers multi-camera rigs, time synchronization across sensors, perception latency budgets, and production deployment of perception pipelines.

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Deploy differential privacy in production systems including epsilon selection strategies, noise calibration with Laplace and Gaussian mechanisms, privacy budget tracking, composition theorems, and Python implementation patterns. Covers both central and local differential privacy models.

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Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.

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Build and audit deterministic verification gates — a check that blocks a pipeline and can be shown to go red. Use when writing a calibration gate, CI check, validation script or pre-publication check for a numeric or empirical result; when a plausible-but-wrong value would survive review; when asking whether an existing test, linter rule or check could actually fail; and when a suite passes first try, passes suspiciously often, or was written by whatever produced the thing it checks. Triggers on "can this check fail", "known-bad", "negative control", "calibration gate", "sanity check my results", "is this test actually testing anything".

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。

Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.

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。

Reads a model's own uncertainty from token log-probabilities: collecting and aggregating label logprobs, confidence tiers and margins for triage, calibration against human labels (ECE, Brier, reliability diagrams), downstream use, and reproducibility. Use for per-item classifier confidence or routing low-confidence cases to human review; codebook and validation design go to text-classification.

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Feed actual task results back into agent memory for calibration. Compares predicted vs actual outcomes, records accuracy scores, and tracks estimation quality, prediction quality, and decision quality over time to improve future agent performance.

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Diagnoses and fixes Claude behavioral issues in system prompts and Projects using tested countermeasure templates. Use when "Claude is too verbose," "keeps hedging," "agrees with everything," "claims it did something it didn't," "won't use a tool," "fix Claude's output," "tune Claude's behavior," "Claude ignores my preferences," "adds unsolicited disclaimers," "uses too many lists." Covers ten tendencies: agreeableness (output-content + persistent-preference), hedging, verbosity, list overuse, fabricated precision, over-exploration, tool miscalibration (over- and under-triggering), LaTeX defaulting, editorial drift, self-referential fabrication. Also use when auditing a system prompt for behavioral calibration or recalibrating a pre-4.7 prompt, and when users describe recurring output problems without naming a tendency. Do NOT use for scoring a prompt's overall quality — use rootnode-prompt-validation if available.

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Epistemic transparency — acknowledging uncertainty, flagging limitations, avoiding overconfidence, and communicating what is known, unknown, and uncertain with proportional confidence. Maps the HEXACO personality dimension to AI reasoning: truthful calibration of confidence, proactive disclosure of gaps, and resistance to the temptation to appear more certain than warranted. Use before presenting a conclusion, when answering questions where knowledge is partial or inferred, after noticing a temptation to state uncertain information as certain, or when a user is making decisions based on provided information.

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AI relational calibration — reading and adapting to the specific person you are working with. Goes beyond user-intent alignment (solving the right problem) to genuine attunement (meeting the person where they are). Maps communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Use at the start of a new session, when communication feels mismatched, after receiving unexpected feedback, or when transitioning between very different users or contexts.

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Design and audit PFC 5.0 wall servo, loading-rate control, equilibrium checks, micro-to-macro calibration, two-target local solves, DOE campaigns, and independent confirmation for asphalt models.

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Facilitate talent review and people decisions with a structured view of performance, potential, readiness, risks, and development actions using talent calibration and 9-box logic. Use when preparing talent review, succession planning, promotion readiness, or performance calibration sessions. Do not use for payroll administration, HRIS updates, or generic praise notes.

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Diagnose when intuitive judgment, agent confidence, or expert routing can be trusted by classifying environment validity, feedback quality, and task-boundary fit. Use for confidence calibration, agent routing, expertise audits, and escalation design. NOT for deterministic implementation tasks, pure syntax debugging, or domains with explicit verifiable answers.

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Reassesses annually the patient’s use of self-monitoring blood glucose to calibrate the CGM system. Triggered by ‘Yearly calibration practice review’ or ‘Annual check of SMBG calibration adherence’.

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Expert-level analytical chemistry knowledge. Use when working with chromatography, spectroscopy, electroanalytical methods, sample preparation, quantitative analysis, calibration, statistics, or instrumental analysis. Also use when the user mentions 'HPLC', 'GC', 'mass spectrometry', 'atomic absorption', 'ICP', 'titration', 'calibration curve', 'detection limit', 'NMR', 'chromatography', 'electrochemistry', 'sample preparation', or 'method validation'.

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Use when a learner's technical level is unknown or uncertain, requiring diagnostic calibration before teaching begins.

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Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정.

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Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.

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Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.

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Designs and validates quantitative targeted metabolomics assays (MRM/SRM on triple-quadrupole, PRM on high-resolution instruments) to report absolute concentrations. Covers the internal-standard strategy (external cal -> global IS -> standard addition -> stable-isotope-labeled IS), weighted calibration judged by back-calculated %RE not R-squared, ion-ratio quantifier/qualifier confirmation, matrix-effect/recovery characterization, and ICH M10 method validation. Use when quantifying a closed panel of known metabolites with units, building or validating an LC-MS/MS assay, choosing an IS or calibration weighting, or judging whether a reported concentration is trustworthy. For untargeted feature detection see metabolomics/xcms-preprocessing; for group statistics see metabolomics/statistical-analysis; for flux/MID/tracing see metabolomics/isotope-tracing.

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Quarterly Silicon Agent performance evaluation with ByteDance-style calibration, forced distribution ranking, dual-track (technical/management) assessment, and automated score calculation. Includes real evaluation forms, calibration meeting scripts, and PIP templates.

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7-agent paper review system on Hermes Agent. 6 modes (full/re-review/quick/methodology-focus/guided/calibration). 5-panel review with editorial decision, revision roadmap, and calibration metrics. Uses delegate_task for each reviewer. Triggers: review paper, peer review, manuscript review, check revisions, calibrate reviewer, 審稿, 同儕審查, 論文審查.

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。