{"id":"W4289527146","doi":"10.1016/j.identj.2022.06.004","title":"Accuracy of the Intraoral Scanner for Detection of Tooth Wear","year":2022,"lang":"en","type":"article","venue":"International Dental Journal","topic":"Dental Erosion and Treatment","field":"Dentistry","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Faculty of Dentistry, McGill University","keywords":"Scanner; Sandpaper; Tooth surface; Dentistry; Materials science; Anterior teeth; Medicine; Orthodontics; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003235871,0.0004285367,0.0003560488,0.001067905,0.0001874908,0.0008483649,0.0005827828,0.001062412,0.001414295],"category_scores_gemma":[0.01054709,0.0003572183,0.0002284069,0.0002351728,0.0004609793,0.0004628572,0.0004664462,0.0003790482,0.0007966661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000138938,"about_ca_system_score_gemma":0.0002545092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003918344,"about_ca_topic_score_gemma":0.000851012,"domain_scores_codex":[0.9965959,0.001273308,0.0002396164,0.0005834719,0.00119039,0.0001172645],"domain_scores_gemma":[0.9929057,0.003881065,0.0008900025,0.0006868116,0.001506839,0.0001295601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002547047,0.0001803442,0.6073043,0.0006116688,0.0002005185,0.0005747437,0.0004581632,0.0006358497,0.2156563,0.0002121547,0.0005881405,0.1710306],"study_design_scores_gemma":[0.00006236562,0.003083526,0.7831516,0.000332254,0.0004941328,0.01839642,0.0008356611,0.01307559,0.1728952,0.0003951459,0.00718859,0.00008965997],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9558768,0.01413114,0.02432792,0.0001565112,0.0001244016,0.00007468886,0.0001762516,0.0002291859,0.004903088],"genre_scores_gemma":[0.9803417,0.001426514,0.01683682,0.00007230364,0.00003413428,0.00002456383,0.0001319912,0.00002631723,0.001105824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003235871,"threshold_uncertainty_score":0.01711315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465687291302596,"score_gpt":0.2948285806857392,"score_spread":0.2801717077727132,"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."}}