「proportionality」の検索結果

Generates complete FAERS-style pharmacovigilance disproportionality research designs from a user-provided drug class, comparator strategy, adverse-event domain, and patient-group stratification. Always use this skill whenever a user wants to design, plan, or build a spontaneous-report safety signal study using FAERS or a similar pharmacovigilance database, especially when the article logic includes product selection, indication-group stratification, MedDRA-based adverse-event extraction, serious-case filtering, suspect-drug and concomitant-exclusion logic, reporting odds ratio analysis, comparator-drug benchmarking, cross-drug comparison, and cautious signal interpretation without causal overclaiming. Covers five study patterns (single-drug disproportionality workflow, multi-drug class comparison workflow, indication-stratified workflow, comparator-controlled signal screening workflow...

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。

Implements email and internet monitoring compliance in the workplace per Barbulescu v Romania (ECHR Grand Chamber), EDPB guidance, and national labour law. Covers acceptable use policies, legitimate expectation of privacy, proportionality testing, and content vs metadata monitoring. Keywords: email monitoring, Barbulescu, workplace privacy, internet monitoring, acceptable use policy, ECHR, proportionality.

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。

Establishes boundaries for monitoring remote and hybrid workers including screen capture, productivity tracking, camera and microphone activation, attendance verification, and activity logging. Applies proportionality principles, transparency requirements, and evaluates less intrusive alternatives per EDPB and national DPA guidance. Keywords: remote work, monitoring, screen capture, productivity tracking, webcam, home office, hybrid work, proportionality, surveillance.

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。

Conducts Data Protection Impact Assessments for employee monitoring systems per EDPB Guidelines 3/2019 on workplace data processing. Covers video surveillance, email monitoring, GPS tracking, keystroke logging, and productivity tools. Applies proportionality testing under Art. 35 GDPR. Keywords: DPIA, employee monitoring, surveillance, proportionality, EDPB, workplace privacy, keystroke logging, GPS tracking.

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。

Conducts retention impact assessments for new processing activities to determine appropriate data retention periods. Covers regulatory requirements scanning, proportionality review, purpose-based retention determination, and retention period documentation aligned with GDPR Article 5(1)(e) and Article 25 data protection by design. Activate for retention assessment, new processing retention, retention period determination queries.

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。

Guides the three-part Legitimate Interest Assessment (LIA) required under GDPR Article 6(1)(f): purpose test, necessity test, and balancing test. Activate when evaluating legitimate interest as a lawful basis, conducting LIA reviews, or documenting proportionality analysis. Keywords: LIA, legitimate interest, balancing test, necessity test, purpose test, Article 6(1)(f).

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。

Manages privacy compliance for employee background checks including criminal record processing under Art. 10 GDPR, DBS checks (UK), national law variations, and reference verification. Applies proportionality and data minimisation to pre-employment screening, defines retention limits, and addresses role-based necessity assessments. Keywords: background check, criminal record, Art. 10, DBS, pre-employment screening, vetting, data minimisation, proportionality.

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。

Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.

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。

Detects and removes doublets/aggregates from flow, spectral, and mass cytometry before clustering or quantification. Covers FSC-A vs FSC-H singlet discrimination (the Area-Height non-proportionality, not a 1D area gate), FSC-W/SSC width gating, CyTOF Gaussian discrimination parameters (Center/Offset/Width/Residual/Event_length) and DNA intercalator gating, and the residual heterotypic conjugates that survive scatter gating and masquerade as double-positive populations. Use when filtering aggregates before phenotyping, choosing a doublet method for flow vs CyTOF, or diagnosing a suspicious double-positive cluster.

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。

GDPR Legitimate Interest Assessment (LIA) — Guided assessment for Art. 6(1)(f) GDPR using the EDPB three-step test. Based on EDPB Guidelines 1/2024, EDPB Opinion 28/2024 (AI models), the OSS Case Digest on Legitimate Interest (McIntyre 2026), CNIL AI guidance (June 2025), ICO guidance, and key CJEU case law. Use when: (1) user needs to assess whether legitimate interest is appropriate, (2) user asks about Art. 6(1)(f), "Interessenabwägung", "berechtigtes Interesse", "balancing test", or "LIA", (3) user wants to document a legitimate interest assessment, (4) user mentions the three-step test, (5) user evaluates necessity or proportionality under Art. 6(1)(f), (6) user discusses direct marketing, fraud prevention, IT security, employee monitoring, AI training, web scraping, or credit checks in context of legal basis, (7) user handles a right to object (Art. 21), (8) user asks about children's data, profiling, or cross-border data sharing under legitimate interest, (9) user compares legitimate interest against other legal bases. Do NOT use for: consent assessments (Art. 6(1)(a)), contract performance (Art. 6(1)(b)), DPIA workflows, or pure ePrivacy/cookie compliance questions — though the skill does address the ePrivacy/GDPR overlap where relevant.

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。

Assess whether a Fundamental Rights Impact Assessment (FRIA) is required under Article 27 EU AI Act, and structure or draft that assessment for a specific high-risk AI deployment. Covers deployer scope gating (public bodies and private entities providing public services), affected group mapping, Charter rights analysis, proportionality, safeguards evaluation, residual risk, DPIA/FRIA cross-referencing under the amended Article 27(4), the unconditional notification duty under Article 27(3), and DACH-specific considerations. Use when asked about FRIA obligations, Article 27 scope, fundamental rights and AI, or deployer assessment duties.

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。

Matter budgeting and ongoing WIP/variance monitoring. Build phase-based fee estimates at matter setup, run bottom-up budgets by jurisdiction or workstream, calculate contingency, and structure AFA arrangements (fixed fee, capped fee, phased fixed fees). Ongoing monitoring: WIP tracking against budget, proportionality assessment (spend vs progress), variance commentary with root cause analysis, forecast-to-complete, realisation monitoring, write-off analysis. Trigger on: 'build a budget', 'fee estimate', 'what will this cost', 'WIP review', 'budget vs actual', 'how are we tracking against budget', 'we're over budget', 'realisation is poor', 'what's our ETC', 'budget for the German workstream', 'model the financial impact of this scope change', 'draft a fee adjustment', 'write-off analysis', 'how much contingency', 'AFA structure', 'fixed fee estimate', 'budget update', 'forecast to complete'.

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。

Guides privacy impact assessment for emerging technologies including IoT, blockchain, AR/VR, quantum computing, and digital twins. Covers risk identification methodology, proportionality assessment, and technology-specific privacy challenges. Activate when evaluating new technology adoption, innovation projects, or emerging tech procurement. Keywords: PIA, emerging technology, IoT, blockchain, AR/VR, quantum computing, digital twins, innovation privacy.

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。

Guides DPIA for workplace monitoring including email surveillance, internet usage monitoring, CCTV, GPS tracking, and keystroke logging. Covers GDPR Art. 88 employment context provisions, WP29 Opinion 2/2017 on data processing at work, and proportionality balancing for employee monitoring. Keywords: employee surveillance, workplace monitoring, DPIA, Art. 88, WP29 Opinion 2/2017, CCTV, email monitoring, GPS tracking.

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。

Detects and removes doublets/aggregates from flow, spectral, and mass cytometry before clustering or quantification. Covers FSC-A vs FSC-H singlet discrimination (the Area-Height non-proportionality, not a 1D area gate), FSC-W/SSC width gating, CyTOF Gaussian discrimination parameters (Center/Offset/Width/Residual/Event_length) and DNA intercalator gating, and the residual heterotypic conjugates that survive scatter gating and masquerade as double-positive populations. Use when filtering aggregates before phenotyping, choosing a doublet method for flow vs CyTOF, or diagnosing a suspicious double-positive cluster.

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 project or processing description and returns a DRAFT data protection impact assessment pack: processing description, necessity and proportionality questions, a risk table with blank rating cells, mitigations to consider and open questions. Never rates risk, determines the lawful basis or judges adequacy; the DPO assesses and signs. Works from descriptions, never personal data. Use when the user asks to "start a DPIA for the new monitoring tool", "draft a data protection impact assessment", "scaffold a DPIA from this processing description" or "what would the DPO need for a DPIA on this". Do not use for redacting or de-identifying a document, use document-deidentification-pass instead; do not use for working out what data an incident exposed, use data-incident-impact-brief instead. Drafts for human review; never approves, authorises or signs off.

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。

Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.

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。

Detects and removes doublets/aggregates from flow, spectral, and mass cytometry before clustering or quantification. Covers FSC-A vs FSC-H singlet discrimination (the Area-Height non-proportionality, not a 1D area gate), FSC-W/SSC width gating, CyTOF Gaussian discrimination parameters (Center/Offset/Width/Residual/Event_length) and DNA intercalator gating, and the residual heterotypic conjugates that survive scatter gating and masquerade as double-positive populations. Use when filtering aggregates before phenotyping, choosing a doublet method for flow vs CyTOF, or diagnosing a suspicious double-positive cluster.

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。

Detects and removes doublets/aggregates from flow, spectral, and mass cytometry before clustering or quantification. Covers FSC-A vs FSC-H singlet discrimination (the Area-Height non-proportionality, not a 1D area gate), FSC-W/SSC width gating, CyTOF Gaussian discrimination parameters (Center/Offset/Width/Residual/Event_length) and DNA intercalator gating, and the residual heterotypic conjugates that survive scatter gating and masquerade as double-positive populations. Use when filtering aggregates before phenotyping, choosing a doublet method for flow vs CyTOF, or diagnosing a suspicious double-positive cluster.

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。