{"id":"W4396693664","doi":"10.2139/ssrn.4818939","title":"Geometric Insights into Focal Loss: Reducing Curvature for Enhanced Model Calibration","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Curvature; Calibration; Computer science; Geometry; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007399561,0.001412767,0.0006478031,0.0006421109,0.0004171227,0.001156075,0.001252477,0.001440697,0.003476418],"category_scores_gemma":[0.004650985,0.0005761093,0.0006855962,0.0005163279,0.0009087342,0.002198072,0.00229737,0.002062955,0.0008233928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007650152,"about_ca_system_score_gemma":0.0007265782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002435247,"about_ca_topic_score_gemma":0.002401004,"domain_scores_codex":[0.9995865,0.0001068664,0.00001710639,0.0001117922,0.0001389769,0.00003867227],"domain_scores_gemma":[0.9991224,0.0002427915,0.0001302109,0.0003193205,0.0001473568,0.00003789428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001210748,0.00006074632,0.001228332,0.0001282362,0.00006956866,0.0001233136,0.0001129088,0.7764115,0.03022485,0.06516428,0.003236429,0.1231187],"study_design_scores_gemma":[0.000004503863,0.00001563925,0.0003192232,0.000007282227,0.000007473264,0.00005532832,0.00001035423,0.9735628,0.003918114,0.02105595,0.001030787,0.00001242586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01885255,0.0001271206,0.9776488,0.0003682754,0.00003033366,0.00001565154,0.00009899466,0.0004520355,0.002406262],"genre_scores_gemma":[0.716172,0.000505136,0.2765692,0.0002843491,0.0000992688,0.00005917183,0.0004065212,0.0006255296,0.005278863],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003476418,"threshold_uncertainty_score":0.01162976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191006588006095,"score_gpt":0.2676758220332803,"score_spread":0.2557657561532193,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}