What frameworks does this skill use for assessment?

The skill utilizes the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) and Cochrane Risk of Bias (ROB) frameworks to evaluate evidence quality.

Is this skill useful for academic peer review?

Absolutely. It provides a structured framework to critique research designs, measurement quality, and the logical consistency of conclusions.

Does it support visual data representation?

While the core skill focuses on analysis, it is designed to work with the scientific-schematics tool to generate flowcharts and bias assessment diagrams.

Can this skill help identify p-hacking or statistical errors?

Yes, it evaluates p-value interpretation, sample size adequacy, multiple comparison corrections, and potential p-hacking or selective reporting.

Scientific Critical Thinking

Name: Scientific Critical Thinking
Author: K-Dense-AI

byK-Dense-AI

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235

数据科学与机器学习

Evaluates research rigor, statistical validity, and methodology to ensure scientific claims are robust and unbiased.

关于

The Scientific Critical Thinking skill empowers Claude to perform high-level analytical reviews of research papers and experimental designs. By applying systematic frameworks like GRADE and Cochrane Risk of Bias, it identifies confounding variables, detects researcher bias, and assesses the strength of evidence in systematic reviews. This skill is essential for researchers and data scientists who need to validate the integrity of scientific claims, interpret complex statistical results, and ensure that experimental methodologies align with industry-standard best practices.

主要功能

Identification of logical fallacies in scientific arguments
Systematic bias and confounding variable detection
Rigorous methodology and experimental design critique
Evidence quality assessment using GRADE and Cochrane ROB
Comprehensive statistical validity and p-value evaluation
235 GitHub stars

使用场景

Designing robust experimental protocols with minimized risk of bias
Performing meta-analyses and systematic evidence synthesis
Conducting peer reviews and critical appraisals of scientific manuscripts

关于

主要功能

Identification of logical fallacies in scientific arguments
Systematic bias and confounding variable detection
Rigorous methodology and experimental design critique
Evidence quality assessment using GRADE and Cochrane ROB
Comprehensive statistical validity and p-value evaluation
235 GitHub stars

使用场景

Designing robust experimental protocols with minimized risk of bias
Performing meta-analyses and systematic evidence synthesis
Conducting peer reviews and critical appraisals of scientific manuscripts