{"id":"W4404724065","doi":"10.1016/j.jebdp.2024.102058","title":"DEEP LEARNING-DRIVEN SEGMENTATION OF DENTAL IMPLANTS AND PERI-IMPLANTITIS DETECTION IN ORTHOPANTOMOGRAPHS: A NOVEL DIAGNOSTIC TOOL","year":2024,"lang":"en","type":"article","venue":"Journal of Evidence Based Dental Practice","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Peri-implantitis; Medicine; Dentistry; Orthodontics; Implant; Surgery","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001162801,0.0002113114,0.0003243972,0.0009342646,0.0001047922,0.0003379752,0.0001824496,0.00009195598,0.00007000657],"category_scores_gemma":[0.003207408,0.0001882048,0.0002398157,0.0008803871,0.0001188336,0.005490039,0.000057762,0.0006936115,0.00001939714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001410626,"about_ca_system_score_gemma":0.00007728043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002960046,"about_ca_topic_score_gemma":0.0004893813,"domain_scores_codex":[0.9974993,0.0003191578,0.0008732842,0.0002868977,0.0007619892,0.0002593541],"domain_scores_gemma":[0.9950264,0.00389648,0.0006887158,0.0001149478,0.0001585973,0.0001148979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001205852,0.0004723195,0.6946657,0.0005601611,0.0002778803,0.006444731,0.0006226919,0.0009208598,0.2343521,0.00003519596,0.00007877804,0.0603638],"study_design_scores_gemma":[0.003157655,0.001638865,0.8329719,0.007334535,0.001082776,0.07750323,0.01049559,0.02458775,0.03988972,0.00004680004,0.0006580945,0.0006330953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768932,0.006768083,0.01467891,0.00007388432,0.001257475,0.0002299343,0.00001707229,0.00002620883,0.00005520273],"genre_scores_gemma":[0.9959706,0.001998687,0.001752384,0.0001015193,0.000117287,0.000008475142,0.000005954527,0.00002629406,0.00001876273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1944623,"threshold_uncertainty_score":0.7674769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02804756659920392,"score_gpt":0.3248012503099994,"score_spread":0.2967536837107955,"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."}}