hypothesis-generation
Generate Scientific Hypotheses
๋ํ ๋ค์์์ ์ฌ์ฉํ ์ ์์ต๋๋ค: davila7
Transform observations into structured, testable scientific hypotheses. This skill guides you through literature synthesis, mechanism development, experimental design, and prediction formulation using proven scientific method frameworks.
์คํฌ ZIP ๋ค์ด๋ก๋
Claude์์ ์ ๋ก๋
์ค์ โ ๊ธฐ๋ฅ โ ์คํฌ โ ์คํฌ ์ ๋ก๋๋ก ์ด๋
ํ ๊ธ์ ์ผ๊ณ ์ฌ์ฉ ์์
ํ ์คํธํด ๋ณด๊ธฐ
"hypothesis-generation" ์ฌ์ฉ ์ค์ ๋๋ค. Generate hypotheses for why certain cancer patients respond to immunotherapy while others do not.
์์ ๊ฒฐ๊ณผ:
- Hypothesis 1 (Blue): Tumor mutational burden determines response - patients with high TMB have more neoantigens that immune cells can recognize
- Hypothesis 2 (Green): T-cell inflamed microenvironment - pre-existing T-cell infiltration indicates receptive immune environment
- Hypothesis 3 (Purple): Microbiome composition - specific gut bacteria enhance checkpoint inhibitor efficacy
- Key prediction: If microbiome hypothesis is correct, fecal transplant from responders should transfer responsiveness
- Discriminating experiment: Compare gene expression profiles of responders vs non-responders to identify signature
"hypothesis-generation" ์ฌ์ฉ ์ค์ ๋๋ค. Create hypotheses for why certain plants survive drought conditions better than others of the same species.
์์ ๊ฒฐ๊ณผ:
- Hypothesis 1 (Deep Blue): Deep root system access - superior water retrieval from lower soil layers during drought periods
- Hypothesis 2 (Forest Green): Stomatal regulation efficiency - enhanced leaf-level water conservation through rapid stomatal closure
- Hypothesis 3 (Royal Purple): Osmotic adjustment capacity - cellular solute accumulation maintains turgor under water stress
- Testable prediction: Deep root hypothesis predicts positive correlation between root depth and survival rate under drought
- Experimental design: Controlled drought trial with root imaging to measure depth correlation
๋ณด์ ๊ฐ์ฌ
์์ This is a pure documentation skill containing only markdown files, LaTeX templates, and reference guides. No executable code exists. All 273 static findings are false positives: backticks in markdown code blocks were misidentified as shell commands, RGB color definitions were misidentified as cryptographic algorithms, and file references were misidentified as reconnaissance.
์ํ ์์ธ
โ๏ธ ์ธ๋ถ ๋ช ๋ น์ด (152)
๐ ๋คํธ์ํฌ ์ ๊ทผ (7)
ํ์ง ์ ์
๋ง๋ค ์ ์๋ ๊ฒ
Research Proposal Development
Develop rigorous hypotheses for thesis proposals with proper experimental designs and literature grounding.
Grant Proposal Hypotheses
Structure compelling testable hypotheses with clear predictions for funding applications.
Hypothesis-Driven Analysis
Formulate hypotheses from exploratory data analysis before confirmatory statistical testing.
์ด ํ๋กฌํํธ๋ฅผ ์ฌ์ฉํด ๋ณด์ธ์
Use the hypothesis-generation skill to create 3-5 testable hypotheses for the following phenomenon: [describe observation or data pattern]. Include mechanistic explanations, supporting evidence from literature, and experimental designs to test each hypothesis.
Apply the hypothesis-generation skill to explain the mechanism of [phenomenon]. Generate competing mechanistic hypotheses, design experiments to distinguish between them, and propose specific quantitative predictions for each.
Use hypothesis-generation to develop novel hypotheses about [research question]. Ground each hypothesis in evidence from PubMed literature, identify gaps in current understanding, and design experiments that would advance the field.
Generate a comprehensive hypothesis report using the hypothesis-generation skill. Include: 3-5 competing hypotheses with mechanistic explanations, testable predictions in amber boxes, comparison boxes showing how to distinguish hypotheses, and detailed experimental designs in appendices. Use the LaTeX template format.
๋ชจ๋ฒ ์ฌ๋ก
- Start with comprehensive literature search to ground hypotheses in existing evidence before formulation
- Ensure each hypothesis makes distinct, testable predictions that can distinguish it from alternatives
- Include falsification criteria for every prediction to maintain scientific rigor
ํผํ๊ธฐ
- Generating vague hypotheses without specific quantitative predictions
- Ignoring contradictory evidence or alternative explanations
- Skipping the experimental design phase - hypotheses must be testable
์์ฃผ ๋ฌป๋ ์ง๋ฌธ
What is the difference between this skill and scientific-brainstorming?
Does this skill search PubMed automatically?
Can I use this for non-biological sciences?
What format does the output use?
How many hypotheses should I generate?
What makes a hypothesis testable?
๊ฐ๋ฐ์ ์ธ๋ถ ์ ๋ณด
์์ฑ์
K-Dense-AI๋ผ์ด์ ์ค
MIT license
๋ฆฌํฌ์งํ ๋ฆฌ
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/hypothesis-generation์ฐธ์กฐ
main
ํ์ผ ๊ตฌ์กฐ
๐ assets/
๐ FORMATTING_GUIDE.md
๐ hypothesis_generation.sty
๐ hypothesis_report_template.tex
๐ references/
๐ experimental_design_patterns.md
๐ hypothesis_quality_criteria.md
๐ literature_search_strategies.md
๐ SKILL.md