{"id":"W4416963159","doi":"10.1109/embc58623.2025.11252946","title":"Automated Cavity Detection and Classification Using Deep Learning","year":2025,"lang":"en","type":"article","venue":"","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University","funders":"McGill University","keywords":"Deep learning; Segmentation; Test set; Pattern recognition (psychology); Set (abstract data type); Training set; Precision and recall; Binary classification; Image segmentation","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001108099,0.001015099,0.0008656885,0.001619597,0.000387422,0.001354971,0.00150428,0.001301203,0.003044455],"category_scores_gemma":[0.001902026,0.000576833,0.001040369,0.000671721,0.0005105238,0.001115697,0.001452277,0.001061769,0.001539506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007628378,"about_ca_system_score_gemma":0.001051572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004481736,"about_ca_topic_score_gemma":0.01018541,"domain_scores_codex":[0.9994069,0.00007433763,0.0000318244,0.0001895324,0.0001961867,0.0001011299],"domain_scores_gemma":[0.9993066,0.0002175472,0.00008024837,0.0001041815,0.0002475119,0.00004392197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003413896,0.0002528297,0.009264818,0.0002984977,0.0001334964,0.0002142398,0.0001353549,0.08273558,0.05129088,0.002040923,0.008570543,0.8447215],"study_design_scores_gemma":[0.00001869574,0.0001041656,0.00308802,0.00004798207,0.00003723447,0.0001921644,0.0000655032,0.9711114,0.01900355,0.003185734,0.003117341,0.00002817534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1423584,0.001853578,0.8389992,0.0005892536,0.000210369,0.0002623997,0.0009355102,0.009815406,0.004975757],"genre_scores_gemma":[0.6314591,0.0008463319,0.3573047,0.0005399128,0.00008750684,0.000195025,0.001856997,0.0004457649,0.007264795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004481736,"threshold_uncertainty_score":0.01018471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01638440460703308,"score_gpt":0.29363714645973,"score_spread":0.2772527418526969,"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."}}