Round UUID: 0b1f9a83-cfaf-45ba-9565-b224a46802c3
Prompt:
Using the provided entity data, classify the entity as either 'Fylaran' or 'Qtharri' by strictly adhering to the following clearly defined rules: 1. **Classify as 'Qtharri' if any of the following conditions are met:** - Mean tidal distortion > 500 AND Mean core density < 0.85 AND Mean axial symmetry >= 250. - Mean tidal distortion >= 450 AND Mean impact crater count < 0.85 AND Mean core density < 0.85. - Mean tidal distortion >= 400 AND Mean ring system complexity < 0.90 AND Mean axial symmetry >= 300. - Mean axial symmetry > 450 AND Mean tidal distortion > 350 AND Mean core density < 0.90. - Mean orbital radius > 3.0 AND Mean surface roughness > 460. - Mean core density < 0.75 AND Mean axial symmetry < 250. - Mean magnetosphere extent < 4.5 AND Mean tidal distortion < 300. - Mean impact crater count < 0.75 AND Mean axial symmetry > 300. - Mean tidal distortion < 30, regardless of other conditions. - Mean tidal distortion between 300 and 450 AND Mean core density < 0.80. 2. **Classify as 'Fylaran' if any of the following conditions are met:** - Mean tidal distortion < 150 AND Mean core density > 0.90 AND Mean axial symmetry <= 300. - Mean tidal distortion > 200 AND Mean core density > 0.90 AND Mean axial symmetry < 400. - Mean impact crater count >= 0.85 AND Mean core density > 0.85 AND Mean tidal distortion < 200. - Mean core density > 0.90 AND Mean tidal distortion < 100 AND Mean axial symmetry > 200. - Mean tidal distortion < 250 AND Mean core density >= 0.85 AND Mean axial symmetry <= 250. - Mean core density > 0.95 AND Mean impact crater count >= 0.90. 3. **Implement very strict boundaries around key thresholds** of Mean core density (0.75, 0.80, 0.85, 0.90) and Mean impact crater count (<0.75, 0.75-0.85, >0.85) to eliminate overlap between classifications and enhance clarity in thresholds. 4. **Continuously evaluate and adjust thresholds** and classification conditions based on updated performance data and confusion matrices to systematically refine and reduce classification errors.