Add Confidence Head to Single Track Finder: Proposal B: Track Correctness Confidence Head (Prediction Level)

[anveshmy]

Purpose
Estimate whether the produced track is a valid, well reconstructed physical track.
This corresponds to the intuitive notion of a confidence score.

Output

• Single scalar confidence logit (sigmoid)

Target Definition
Identify the hit overlap between the predicted track and the best matching ground truth track, using either a binary threshold or the overlap score itself as a soft label.

Let:

• P be the set of predicted hits
• Gk be the set of hits for GT track k

Define hit overlap:

• Precision = |P ∩ Gk| / |P|
• Recall = |P ∩ Gk| / |Gk|
• F1 = 2PR / (P + R)

Match prediction to best GT track:

• k* = argmax_k F1(P, Gk)

Label options:

• Soft label (recommended): y = F1(P, Gk*)

Loss

• BCE (hard or soft target) or MSE (soft target) between soft label calculated above and model's confidence score prediction
• Weighted conservatively relative to reconstruction losses

Evaluation

• Accuracy and precision recall (hard labels)
• Correlation with F1, residuals, and momentum error
• Reconstruction quality vs confidence threshold

Notes
Ground truth overlap is used only to generate training targets.
At inference, confidence is predicted solely from the model’s internal track representation.