astoreyai/ai_scientist

Detect AI/LLM-generated text patterns in research writing. Use when: (1) Reviewing manuscript drafts before submission, (2) Pre-commit validation of documentation, (3) Quality assurance checks on research artifacts, (4) Ensuring natural academic writing style, (5) Tracking writing authenticity over time. Analyzes grammar perfection, sentence uniformity, paragraph structure, word frequency (AI-typical words like 'delve', 'leverage', 'robust'), punctuation patterns, and transition word overuse.

Implement blinding procedures to reduce bias in experimental studies. Use when: (1) Designing RCTs, (2) Ensuring objectivity, (3) Meeting CONSORT standards, (4) Minimizing performance and detection bias.

Format citations and bibliographies in multiple academic styles (APA, IEEE, Chicago, Harvard, MLA, Nature, Science). Use when: (1) Converting between citation styles for different journals, (2) Cleaning and standardizing bibliography entries, (3) Validating citation formatting before submission, (4) Generating properly formatted reference lists, (5) Checking citation consistency across manuscripts.

Create publication-quality data visualizations. Use when: (1) Presenting results, (2) Exploratory data analysis, (3) Manuscript preparation, (4) Grant proposals, (5) Presentations.

Calculate and interpret effect sizes for statistical analyses. Use when: (1) Reporting research results to show practical significance, (2) Meta-analysis to combine study results, (3) Grant writing to justify expected effects, (4) Interpreting published studies beyond p-values, (5) Sample size planning for power analysis.

Design rigorous experiments following best practices. Use when: (1) Planning research studies, (2) Grant proposal development, (3) Pre-registration, (4) Ensuring internal validity, (5) Meeting NIH rigor standards.

Guide selection and interpretation of statistical hypothesis tests. Use when: (1) Choosing appropriate test for research data, (2) Checking assumptions before analysis, (3) Interpreting test results correctly, (4) Reporting statistical findings, (5) Troubleshooting assumption violations.

Apply inclusion/exclusion criteria systematically in literature reviews. Use when: (1) Screening abstracts, (2) Reviewing full texts, (3) Documenting screening decisions, (4) Ensuring PRISMA compliance.

Develop IRB/ethics protocols for human subjects research. Use when: (1) Planning studies involving humans, (2) Preparing IRB applications, (3) Ensuring ethical compliance, (4) Addressing informed consent.

Identify research gaps from systematic literature reviews. Use when: (1) Completing literature reviews, (2) Justifying new studies, (3) Grant proposal development, (4) Dissertation planning, (5) Identifying future research directions.

Conduct quantitative synthesis through meta-analysis. Use when: (1) Combining effect sizes across studies, (2) Systematic review synthesis, (3) Calculating summary effects, (4) Assessing heterogeneity.

Calculate statistical power and required sample sizes for research studies. Use when: (1) Designing experiments to determine sample size, (2) Justifying sample size for grant proposals or protocols, (3) Evaluating adequacy of existing studies, (4) Meeting NIH rigor standards for pre-registration, (5) Conducting retrospective power analysis to interpret null results.

Create pre-registration documents for research transparency. Use when: (1) Before data collection, (2) Grant submissions, (3) Ensuring reproducibility, (4) Meeting open science standards, (5) Preventing HARKing.

Generate PRISMA 2020 flow diagrams for systematic reviews. Use when: (1) Conducting systematic literature reviews, (2) Documenting screening process, (3) Reporting study selection for publications, (4) Demonstrating PRISMA compliance, (5) Creating transparent review methodology documentation.

Prepare manuscripts for journal submission. Use when: (1) Writing research papers, (2) Selecting target journals, (3) Formatting manuscripts, (4) Ensuring reporting guideline compliance, (5) Preparing submission materials.

Implement proper randomization procedures for experiments. Use when: (1) Assigning participants to conditions, (2) Ensuring unbiased allocation, (3) Meeting CONSORT standards, (4) Pre-registration.

Formulate research questions using FINER criteria (Feasible, Interesting, Novel, Ethical, Relevant). Use when: (1) Starting new research projects, (2) Refining study scope, (3) Grant proposal development, (4) Ensuring research question quality.

Interpret statistical results correctly and comprehensively. Use when: (1) Writing results sections, (2) Discussing findings, (3) Avoiding common misinterpretations, (4) Reporting effect sizes and confidence intervals.

Assess risk of bias in research studies for systematic reviews. Use when: (1) Conducting systematic reviews, (2) Evaluating study quality, (3) GRADE assessments, (4) Meta-analysis planning.

Conduct sensitivity analyses to test robustness of findings. Use when: (1) Testing assumption violations, (2) Meta-analysis robustness, (3) Handling missing data, (4) Examining outliers.

Conduct subgroup analyses to examine effect moderation. Use when: (1) Testing pre-specified moderators, (2) Exploring heterogeneity, (3) Identifying differential effects, (4) Meta-analysis synthesis.

Create evidence synthesis matrices for systematic reviews. Use when: (1) Organizing extracted data, (2) Comparing study characteristics, (3) Identifying patterns across studies, (4) Preparing synthesis for manuscripts.