Round 305

Round UUID: 9b2dfe62-067a-4419-8e79-fd248cc3bd4b

Prompt:

To classify an entity as Fylaran or Qtharri, use the following refined rules based on the mean attributes, error metrics, and specific thresholds to address edge cases:

1. If 'mean_orbital_radius' is greater than or equal to 3.0 and 'mean_surface_roughness' is greater than or equal to 300, classify as Fylaran unless 'mean_core_density' exceeds 0.91.
2. If 'mean_orbital_radius' is less than 2.6, regardless of other features, classify as Qtharri.
3. If 'mean_core_density' is greater than 0.91, classify as Qtharri.
4. If 'mean_core_density' is less than or equal to 0.85 and 'mean_impact_crater_count' is less than 0.95, classify as Fylaran.
5. If 'mean_orbital_radius' is between 2.6 and 3.0 inclusive, and 'mean_surface_roughness' exceeds 500, classify as Fylaran unless 'mean_core_density' exceeds 0.90 or 'mean_impact_crater_count' exceeds 0.96.
6. If 'mean_surface_roughness' is less than 200 and 'mean_core_density' is between 0.85 and 0.91, classify as Qtharri.

For edge cases and new refinements to address misclassifications:
7. If 'mean_core_density' is between 0.89 and 0.92, then:
    a. If 'mean_surface_roughness' is greater than or equal to 350 and 'core_density_error' is less than 0.1, classify as Fylaran.
    b. If 'mean_surface_roughness' is less than 350 or 'core_density_error' exceeds 0.15, classify as Qtharri.
8. Enhance the weighted scoring system for borderline cases where none of the above rules apply:
    - Calculate the weighted score as follows: (**6×mean_orbital_radius** + **3×mean_surface_roughness** - **4×mean_core_density**) divided by the sum of feature coefficients.
      - If the score exceeds 2.6, classify as Fylaran.
      - Otherwise, classify as Qtharri.
9. Additionally, prioritize:
    - If 'core_density_error' exceeds 0.12 and 'mean_axial_symmetry' is below 110, classify as Qtharri.
    - If 'core_density_error' is less than 0.1 but 'orbital_radius_error' exceeds 0.7, factor in closer proximity to 'mean_orbital_radius' or 'mean_core_density' to determine classification tendency.

This revised prompt adds more granular thresholds for borderline mean_core_density values and adjusts edge case handling to enhance recall and reduce both false positives and false negatives.