Scientific Classification Skill
Classify and categorize scientific content across all disciplines.
When to Use
- "Classify this paper by discipline"
- "What research methodology does this use?"
- "Categorize these results by topic"
- "Assess the quality tier of this journal/paper"
- Sorting literature by approach or field
- Identifying study design type (RCT, cohort, case-control, etc.)
When NOT to Use
- Simple keyword extraction (use scienceclaw-ie)
- Full paper summarization (use scienceclaw-summarization)
- Fact verification (use scienceclaw-verification)
Classification Dimensions
1. Discipline Classification
Classify into one of 17+ primary disciplines and subdisciplines:
- Natural Sciences: Physics, Chemistry, Biology, Medicine, Materials Science, Astronomy, Earth Science, Environmental Science, Agricultural Science
- Formal Sciences: Mathematics, Computer Science
- Social Sciences: Economics, Sociology, Psychology, Political Science, Linguistics
- Humanities: Philosophy, History, Law
2. Methodology Classification
- Empirical: experimental, observational, survey, case study
- Theoretical: mathematical modeling, simulation, analytical
- Computational: data-driven, machine learning, numerical methods
- Review: systematic review, meta-analysis, scoping review, narrative review
- Mixed Methods: combining qualitative and quantitative
3. Study Design Classification
- Randomized controlled trial (RCT)
- Cohort study (prospective/retrospective)
- Case-control study
- Cross-sectional study
- Longitudinal study
- Qualitative study (ethnography, phenomenology, grounded theory)
4. Quality Assessment
- Tier 1: High-quality evidence (large RCTs, systematic reviews with meta-analysis)
- Tier 2: Moderate evidence (cohort studies, well-designed experiments)
- Tier 3: Low evidence (case reports, expert opinion, preliminary studies)
- Tier 4: Pre-print or non-peer-reviewed
Output Format
Always structure classification output as:
**Discipline**: [Primary] > [Subdiscipline]
**Methodology**: [Type]
**Study Design**: [Design type]
**Quality Tier**: [1-4] — [Justification]
**Key Topics**: [topic1, topic2, ...]
**Confidence**: [High/Medium/Low]
Guidelines
- Always provide confidence level for classifications
- Note when content spans multiple disciplines (interdisciplinary)
- Distinguish between primary and secondary methodologies
- Consider journal impact factor and peer-review status for quality assessment
- Flag potential misclassifications or ambiguous cases
- Use standardized vocabulary (MeSH terms for biomedical, ACM CCS for CS, etc.)
1---
2name: scienceclaw-classification
3description: "Classify scientific content by discipline, methodology, topic, and quality. Use when: user asks to categorize papers, methods, or research outputs. NOT for: simple keyword tagging or non-scientific content."
4metadata: { "openclaw": { "emoji": "🏷️" } }
5---
6
7# Scientific Classification Skill
8
9Classify and categorize scientific content across all disciplines.
10
11## When to Use
12
13- "Classify this paper by discipline"
14- "What research methodology does this use?"
15- "Categorize these results by topic"
16- "Assess the quality tier of this journal/paper"
17- Sorting literature by approach or field
18- Identifying study design type (RCT, cohort, case-control, etc.)
19
20## When NOT to Use
21
22- Simple keyword extraction (use scienceclaw-ie)
23- Full paper summarization (use scienceclaw-summarization)
24- Fact verification (use scienceclaw-verification)
25
26## Classification Dimensions
27
28### 1. Discipline Classification
29Classify into one of 17+ primary disciplines and subdisciplines:
30- **Natural Sciences**: Physics, Chemistry, Biology, Medicine, Materials Science, Astronomy, Earth Science, Environmental Science, Agricultural Science
31- **Formal Sciences**: Mathematics, Computer Science
32- **Social Sciences**: Economics, Sociology, Psychology, Political Science, Linguistics
33- **Humanities**: Philosophy, History, Law
34
35### 2. Methodology Classification
36- **Empirical**: experimental, observational, survey, case study
37- **Theoretical**: mathematical modeling, simulation, analytical
38- **Computational**: data-driven, machine learning, numerical methods
39- **Review**: systematic review, meta-analysis, scoping review, narrative review
40- **Mixed Methods**: combining qualitative and quantitative
41
42### 3. Study Design Classification
43- Randomized controlled trial (RCT)
44- Cohort study (prospective/retrospective)
45- Case-control study
46- Cross-sectional study
47- Longitudinal study
48- Qualitative study (ethnography, phenomenology, grounded theory)
49
50### 4. Quality Assessment
51- **Tier 1**: High-quality evidence (large RCTs, systematic reviews with meta-analysis)
52- **Tier 2**: Moderate evidence (cohort studies, well-designed experiments)
53- **Tier 3**: Low evidence (case reports, expert opinion, preliminary studies)
54- **Tier 4**: Pre-print or non-peer-reviewed
55
56## Output Format
57
58Always structure classification output as:
59
60```
61**Discipline**: [Primary] > [Subdiscipline]
62**Methodology**: [Type]
63**Study Design**: [Design type]
64**Quality Tier**: [1-4] — [Justification]
65**Key Topics**: [topic1, topic2, ...]
66**Confidence**: [High/Medium/Low]
67```
68
69## Guidelines
70
711. Always provide confidence level for classifications
722. Note when content spans multiple disciplines (interdisciplinary)
733. Distinguish between primary and secondary methodologies
744. Consider journal impact factor and peer-review status for quality assessment
755. Flag potential misclassifications or ambiguous cases
766. Use standardized vocabulary (MeSH terms for biomedical, ACM CCS for CS, etc.)
beita6969 