{"id":"W2790654286","doi":"10.2319/091117-611.1","title":"Palatal volume and area assessment on digital casts generated from cone-beam computed tomography scans","year":2018,"lang":"en","type":"article","venue":"The Angle Orthodontist","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Superimposition; Cone beam computed tomography; Reproducibility; Volume (thermodynamics); Computed tomography; Intraclass correlation; Tomography; Orthodontics; Mathematics; Medicine; Computer science; Radiology; Artificial intelligence; Physics; Statistics","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":[0.0001756468,0.0002822297,0.0002936952,0.0001444793,0.0004331457,0.0006602809,0.0003084596,0.00007805194,0.0002385234],"category_scores_gemma":[0.00001720684,0.0002234924,0.0001725875,0.0005097044,0.0005366876,0.000350567,0.0001539734,0.0002365972,0.0001649014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002874012,"about_ca_system_score_gemma":0.00002154441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006149323,"about_ca_topic_score_gemma":0.0006001531,"domain_scores_codex":[0.9983954,0.000102078,0.0002956576,0.0004849209,0.0003425876,0.0003792967],"domain_scores_gemma":[0.9989563,0.0001189816,0.0001376508,0.0005401055,0.00009188397,0.0001550834],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001237126,0.0002212511,0.959189,0.00001011449,0.000373052,0.0003728867,0.0002195806,0.000009226084,0.00301664,0.0003624624,0.01969094,0.01641115],"study_design_scores_gemma":[0.0009446276,0.000215296,0.9855944,0.00006998282,0.00008430356,0.0001993413,0.00017841,0.002383421,0.001441634,0.0001524957,0.008378667,0.0003574487],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821104,0.0003195203,0.004063117,0.0001018776,0.0009478784,0.0002461189,0.0008268487,0.0001695571,0.01121468],"genre_scores_gemma":[0.9973195,0.000009541019,0.0006260565,0.0003234351,0.0003745152,0.00001093469,0.0004121991,0.00003893337,0.0008848383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02640539,"threshold_uncertainty_score":0.9113757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981900265060918,"score_gpt":0.2645175780961693,"score_spread":0.2446985754455601,"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."}}