{"id":"W2141534405","doi":"10.1016/j.ajodo.2006.08.024","title":"Three-dimensional accuracy of measurements made with software on cone-beam computed tomography images","year":2008,"lang":"en","type":"article","venue":"American Journal of Orthodontics and Dentofacial Orthopedics","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":240,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Cone beam computed tomography; Landmark; Cone beam ct; Computed tomography; Software; Anatomical landmark; Gold standard (test); Mathematics; Medicine; Nuclear medicine; Orthodontics; Artificial intelligence; Computer science; Radiology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007117643,0.0008944081,0.0006931716,0.00250522,0.0006679393,0.002943801,0.001372983,0.001295443,0.002892095],"category_scores_gemma":[0.03955093,0.0007409931,0.0007277629,0.001302211,0.001004275,0.001415253,0.001798392,0.001175408,0.001008399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008500459,"about_ca_system_score_gemma":0.001299465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004828434,"about_ca_topic_score_gemma":0.006196172,"domain_scores_codex":[0.9927018,0.001235357,0.001524082,0.0009245255,0.003297065,0.0003171469],"domain_scores_gemma":[0.9554182,0.0219151,0.00196631,0.006615933,0.01359663,0.0004878302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004930264,0.0003008874,0.1375133,0.0008253392,0.0005598268,0.0004860023,0.003120017,0.03074243,0.2064237,0.005417365,0.00488867,0.6047922],"study_design_scores_gemma":[0.0002171888,0.0007057402,0.3551734,0.0002783698,0.000805498,0.00316011,0.001334281,0.2841499,0.3330311,0.002787524,0.01772912,0.0006276466],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5676793,0.001776129,0.4119557,0.0003824141,0.0005582682,0.0002091463,0.001948036,0.007106102,0.008384788],"genre_scores_gemma":[0.8597271,0.0003462922,0.1361022,0.00009196576,0.00003401419,0.0001107678,0.001118853,0.001125965,0.001342903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007117643,"threshold_uncertainty_score":0.03764212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02723365798188529,"score_gpt":0.2695361702099734,"score_spread":0.2423025122280881,"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."}}