Classify scientific objects, detect patterns, and categorize data across astronomy, biology, and social sciences
--- name: scientific-classification description: Classify scientific objects, detect patterns, and categorize data across astronomy, biology, and social sciences --- # Scientific Classification & Detection ## Purpose Classify scientific objects and detect patterns using established taxonomies and classification schemes. ## Key Datasets - **SDSS Stellar Classification** (Allanatrix/Astro): 100K objects from SDSS DR17 — Stars, Galaxies, Quasars with photometric features (u, g, r, i, z magnitudes, redshift) - **Social Bias Frames** (allenai/social_bias_frames): Allen AI SBIC corpus for detecting implicit social biases in text ## Protocol 1. **Feature extraction** — Identify relevant features for classification task 2. **Taxonomy mapping** — Map to standard classification scheme 3. **Classification** — Apply appropriate classifier with confidence scores 4. **Validation** — Cross-validate against known labeled examples 5. **Edge case analysis** — Flag ambiguous or borderline cases ## Classification Domains - **Astronomical objects**: Stellar spectral types (OBAFGKM), galaxy morphology (Hubble), AGN types - **Biological taxonomy**: Species classification, protein families, cell types - **Chemical compounds**: Functional groups, drug classes, toxicity levels - **Text classification**: Sentiment, bias detection, topic classification - **Image classification**: Histopathology, satellite imagery, microscopy ## Rules - Report classification confidence and alternative labels - Use domain-standard taxonomies (not ad-hoc categories) - Handle multi-label and hierarchical classification - Document decision boundaries and feature importance--- name: scientific-classification description: Classify scientific objects, detect patterns, and categorize data across astronomy, biology, and social sciences --- # Scientific Classification & Detection ## Purpose Classify scientific objects and detect patterns using established taxonomies and classification schemes. ## Key Datasets - **SDSS Stellar Classification** (Allanatrix/Astro): 100K objects from SDSS DR17 — Stars, Galaxies, Quasars with photometric features (u, g, r, i, z magnitudes, redshift) - **Social Bias Frames** (allenai/social_bias_frames): Allen AI SBIC corpus for detecting implicit social biases in text ## Protocol 1. **Feature extraction** — Identify relevant features for classification task 2. **Taxonomy mapping** — Map to standard classification scheme 3. **Classification** — Apply appropriate classifier with confidence scores 4. **Validation** — Cross-validate against known labeled examples 5. **Edge case analysis** — Flag ambiguous or borderline cases ## Classification Domains - **Astronomical objects**: Stellar spectral types (OBAFGKM), galaxy morphology (Hubble), AGN types - **Biological taxonomy**: Species classification, protein families, cell types - **Chemical compounds**: Functional groups, drug classes, toxicity levels - **Text classification**: Sentiment, bias detection, topic classification - **Image classification**: Histopathology, satellite imagery, microscopy ## Rules - Report classification confidence and alternative labels - Use domain-standard taxonomies (not ad-hoc categories) - Handle multi-label and hierarchical classification - Document decision boundaries and feature importance
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