Research

SOP: 使用 AHRQ PiCMe 框架对研究 gap 进行 6 维度系统评估

SOP: 使用 AHP 层次分析法确定评分维度权重，输出权重向量

Aggregate multiple ranking ballots into a consensus ranking using a specified social choice method.

Construct the strongest possible case for a rejected candidate or counter-position.

Campaign: Logical extreme and boundary testing via reductio ad absurdum and edge-case analysis. Core question: Does this artifact collapse under logical limits and boundary conditions? Methods: Lakatos 1976, Dutilh Novaes 2016, BVA, Flyvbjerg Critical Case, Popper.

Tactic: Construct detailed hostile persona, attack artifact from that persona's perspective, record successful attack paths for aggregation.

Strategy: Role-play attacks from hostile personas — competing lab researcher, hostile reviewer, funding skeptic, domain outsider — each with distinct attack motivations and blind spots.

Strategy: Progressive pressure escalation — starts with surface-level challenges and escalates to fundamental assumption attacks based on defender confidence decay.

Structured debate protocol that constructs an advocate, deploys critic attacks, and renders a judge verdict through iterative rounds.

Iteratively select maximally informative pairs, execute comparisons, update ratings, and check convergence until ranking stabilizes.

Understand who the user is — background, resources, constraints, and deep motivations. Produces an ActorProfile that informs all downstream decisions. Use this tactic at the start of any crystallization process to build a model of the user's capabilities, limitations, and intent.

Enumerate all implementation activities from an experiment design

Compute Risk Priority Number (RPN = S x O x D), classify failure modes into H/M/L action priority per AIAG-VDA tables.

Abstract biological principle to design principle. Bridge from biology to engineering.

Move between concrete and abstract framings — 3 levels up (Why?) and 3 levels down (How?) to find the most productive research level.

Perform bisociation at multiple abstraction levels

Extract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms.

Classify assumptions on 2 axes — load-bearing (how much conclusion depends on it) × vulnerable (how likely to be false). Focuses attention on High-Load × High-Vulnerable quadrant.

Remove components one by one from a system, record the response/impact of each removal.

Design ablation studies to isolate component contributions in ML systems

Map system architecture to ablatable units for ablation studies

Remove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.

Strategy: 面对异常的最佳解释推理

The resource bar now reads token totals from accumulated usage metrics rather than heuristic message counts, keeping the UI aligned with provider-reported usage.