{"id":"W2912174826","doi":"10.1016/j.ortho.2019.01.007","title":"Skeletal and dental relationships in vertical/non-vertical growers using CBCT","year":2019,"lang":"en","type":"article","venue":"International Orthodontics","topic":"Orthodontics and Dentofacial Orthopedics","field":"Dentistry","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Cone beam computed tomography; Horizontal and vertical; Mathematics; Statistical analysis; Orthodontics; Medicine; Computed tomography; Geometry; Statistics; 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":[0.0005942291,0.0002239354,0.0002977853,0.0002538952,0.00007861183,0.0001777977,0.0002315912,0.0002415895,0.0002806825],"category_scores_gemma":[0.000537142,0.0002370785,0.000143122,0.0002240606,0.0001069869,0.0004058486,0.0002268287,0.0005662535,0.0003255381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000159652,"about_ca_system_score_gemma":0.0000772659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001603055,"about_ca_topic_score_gemma":0.0005585753,"domain_scores_codex":[0.997754,0.000113855,0.000610396,0.0004267776,0.0007451411,0.0003498795],"domain_scores_gemma":[0.9990717,0.0002842141,0.00006437467,0.0002548639,0.0001459756,0.0001788274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000566709,0.0001025355,0.9855956,0.00001689794,0.00005788668,0.0002224661,0.00008583986,0.000174257,0.001258875,0.01206393,0.00006757368,0.0002974504],"study_design_scores_gemma":[0.001258843,0.00004385169,0.9541004,0.00006693789,0.00005286107,0.0001932126,0.0001573553,0.04012682,0.0002015214,0.0002311985,0.003246214,0.0003207775],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856284,0.00007074518,0.00647628,0.0001452435,0.002397921,0.0002362665,0.0000221591,0.00004116386,0.004981833],"genre_scores_gemma":[0.9948023,0.00003038462,0.003869491,0.0001473646,0.0001943221,0.000004064634,0.00003853548,0.0000400431,0.0008735078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03995256,"threshold_uncertainty_score":0.9667782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03651861049354288,"score_gpt":0.3122801174990382,"score_spread":0.2757615070054953,"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."}}