{"id":"W7131067550","doi":"10.1111/ocr.70079","title":"Preface to the 10th Biennial <scp>COAST</scp> Conference: <scp>AI</scp> ‐ and Biomedicine‐Driven Precision Orthodontics and Craniofacial Care","year":2025,"lang":"en","type":"article","venue":"Orthodontics and Craniofacial Research","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Craniofacial; Biomedicine; Foundation (evidence); MEDLINE","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002571806,0.0003952228,0.0006611869,0.0006461499,0.001455801,0.0004555283,0.0003172364,0.0004952811,0.00001918493],"category_scores_gemma":[0.007607049,0.0003009382,0.00009457456,0.001296613,0.0008522148,0.0001782787,0.0004951878,0.001217368,0.00002672673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001299065,"about_ca_system_score_gemma":0.0010476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001693801,"about_ca_topic_score_gemma":0.001950224,"domain_scores_codex":[0.9955535,0.0005155977,0.0007481932,0.0009272663,0.001179798,0.001075653],"domain_scores_gemma":[0.9944298,0.002174465,0.0001122666,0.0005907111,0.001900126,0.0007926569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001783712,0.0002041298,0.567799,0.0009052381,0.0001168928,0.00004352127,0.04447756,0.000007596438,0.003621927,0.00463895,0.01578771,0.3622191],"study_design_scores_gemma":[0.001245339,0.002872035,0.4961405,0.001334166,0.000405359,0.00008333869,0.1048329,0.002803435,0.003243944,0.003408671,0.3833598,0.0002704791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823046,0.001327712,0.004304675,0.006549677,0.000966499,0.00217526,0.00006825732,0.00006202827,0.002241259],"genre_scores_gemma":[0.9892128,0.00377141,0.001256868,0.000865353,0.0008255799,0.0001081709,0.00004747105,0.00004682265,0.003865501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3675721,"threshold_uncertainty_score":0.9999443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1490589817163611,"score_gpt":0.4661303404531467,"score_spread":0.3170713587367856,"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."}}