{"id":"W2068587534","doi":"10.1016/j.joms.2009.03.040","title":"Accuracy of Computer Programs in Predicting Orthognathic Surgery Hard Tissue Response","year":2009,"lang":"en","type":"review","venue":"Journal of Oral and Maxillofacial Surgery","topic":"Orthodontics and Dentofacial Orthopedics","field":"Dentistry","cited_by":105,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Orthognathic surgery; Selection (genetic algorithm); Medical physics; Orthodontics; Artificial intelligence; Computer science","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":[0.001883184,0.0008041445,0.001861231,0.001774607,0.0001200841,0.0007974796,0.001272987,0.0006855599,0.001222864],"category_scores_gemma":[0.006281479,0.0003569909,0.0009815056,0.001490781,0.0002986305,0.0006464891,0.0002454816,0.0006764563,0.0004904764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002866411,"about_ca_system_score_gemma":0.0005995007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002953613,"about_ca_topic_score_gemma":0.003849371,"domain_scores_codex":[0.9992773,0.0001368473,0.000132233,0.0001285417,0.0003023507,0.00002275132],"domain_scores_gemma":[0.9935069,0.004800722,0.0005676148,0.0001204663,0.0009560518,0.00004824762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0004799111,0.0002487287,0.07492791,0.008355384,0.001101448,0.0001770885,0.00007306303,0.001373902,0.0008375903,0.0002061609,0.00380812,0.9084106],"study_design_scores_gemma":[0.000612924,0.004730317,0.6606027,0.03099963,0.02198576,0.01360789,0.001030934,0.0344915,0.02634479,0.002336265,0.2027693,0.0004879582],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.04489149,0.948913,0.002436306,0.0003386675,0.0002520292,0.00005329755,0.0004784903,0.00008278932,0.002553945],"genre_scores_gemma":[0.1720929,0.816694,0.007671441,0.0003263537,0.0003187522,0.00006586973,0.001153742,0.00002548141,0.001651498],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002953613,"threshold_uncertainty_score":0.00995934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1271296560082647,"score_gpt":0.3524348942310928,"score_spread":0.2253052382228281,"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."}}