beita6969 / scientific-classification

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/socialbiasframes): 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