scientific-classification

Research

Classify scientific objects, detect patterns, and categorize data across astronomy, biology, and social sciences

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Source SKILL.md: https://github.com/beita6969/ScienceClaw/blob/HEAD/skills/scientific-classification/SKILL.md

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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

Feature extraction — Identify relevant features for classification task
Taxonomy mapping — Map to standard classification scheme
Classification — Apply appropriate classifier with confidence scores
Validation — Cross-validate against known labeled examples
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