Round 306

Round UUID: 67f47d91-0aa1-47ae-a3a8-bcea468f432e

Prompt:

To classify an entity as Fylaran or Qtharri based on refined thresholds, edge adjustments, and weighted scoring:

1. Primary Threshold Rules:
   - If 'mean_orbital_radius' ≥ 3.0 and 'mean_surface_roughness' ≥ 300, classify as Fylaran unless 'mean_core_density' > 0.91 or 'mean_tidal_distortion' > 400.
   - If 'mean_orbital_radius' < 2.6, classify as Qtharri.
   - If 'mean_core_density' > 0.91, classify as Qtharri.
   - If 'mean_core_density' ≤ 0.85 and 'mean_impact_crater_count' < 0.95, classify as Fylaran.
   - If 'mean_orbital_radius' is between 2.6 and 3.0, and 'mean_surface_roughness' > 500, classify as Fylaran unless 'mean_core_density' > 0.89 or 'mean_tidal_distortion' > 250.
   - If 'mean_surface_roughness' < 200 and 'mean_core_density' is between 0.85 and 0.91, classify as Qtharri.

2. Adjusted Details for Mid-Range Cases:
   - If 'mean_orbital_radius' is between 2.8 and 3.0, 'mean_surface_roughness' is between 300 and 450, and 'mean_core_density' is between 0.86 and 0.90:
     a. Prioritize Fylaran classification unless 'core_density_error' > 0.15.
     b. If 'core_density_error' > 0.15 and 'mean_axial_symmetry' ≤ 120, classify as Qtharri.

3. Edge Refinements for Rare Misclassifications:
   - If 'core_density_error' > 0.15 and 'surface_roughness_error' > 1.0, classify as Qtharri.
   - If 'mean_axial_symmetry' > 200 and 'mean_cloud_turbulence' < 150, classify as Fylaran.
   - If 'mean_axial_symmetry' is between 100 and 200, weigh contribution of 'core_density_error' and 'orbital_radius_error' before scoring.

4. Enhanced Weighted Scoring System for Unresolved Edge Cases:
   - Compute score: (**6×mean_orbital_radius** + **2×mean_surface_roughness** - **5×mean_core_density** + **1×mean_impact_crater_count**) divided by the sum of feature coefficients.
      - If score > 2.5, classify as Fylaran.
      - Otherwise, classify as Qtharri.

This revision minimizes misclassifications in ranges identified as problematic and adjusts edge rules for conflicting cases, improving recall and reducing false negatives.