Results for “empiricism”

research-synthesis

Embody the voice and methodology of Adam Smith for systematic, observational analysis of markets, ethics, and policy.

Audits hidden assumptions in decisions or beliefs by classifying them into fact, convention, belief, or interest-driven, ranking by fragility and impact, then rebuilding conclusions from verified premises. Supports English and Chinese.

Turn research inputs into concise evidence, patterns, confidence levels, and product decisions.

Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings. Integrates Apple Health data for personalized context. Use when user asks health, nutrition, exercise, sleep, or wellness questions.

Investigates a question systematically before answering — verifying claims through sources, distinguishing known facts from inferences, and calibrating expressed confidence to actual certainty. Use when asked to research a topic, verify a claim, evaluate a technology, or answer a question where accuracy matters more than speed.

Evaluate scientific claims and evidence quality by assessing experimental design, identifying biases and confounders, and applying evidence grading frameworks like GRADE and Cochrane Risk of Bias.

Design experiments and studies before data collection — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable.

Simulates a NeurIPS/SC/ICSE-style peer review with five reviewer personas (HPC, ML, Stats, Reproducibility, Devil's Advocate) that verify every claim against actual result data before submission.

以证据为先的ECC当前状态研究工作流程。当用户希望基于当前公开证据和提供的本地上下文获取最新事实、比较、丰富信息或建议时使用。