{"id":"W4310570700","doi":"10.2174/1573405619666221130115929","title":"Cone Beam CT Features and Oral Radiologist’s Decision-making ofArrested Pneumatization of the Sphenoid Sinus","year":2022,"lang":"en","type":"article","venue":"Current Medical Imaging Formerly Current Medical Imaging Reviews","topic":"Sinusitis and nasal conditions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Skull; Medicine; Cone beam computed tomography; Radiography; Confidence interval; Sinus (botany); Radiology; Dentistry; Nuclear medicine; Computed tomography; Anatomy; Internal medicine","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":[0.003063625,0.0002994721,0.0002286217,0.002648433,0.0002892668,0.001004757,0.0004700909,0.00071951,0.002358081],"category_scores_gemma":[0.02006815,0.0002460301,0.0003364355,0.0006318191,0.0005554617,0.0009890735,0.0006045227,0.0003514644,0.0004316079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002751828,"about_ca_system_score_gemma":0.0003826011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001736544,"about_ca_topic_score_gemma":0.002128686,"domain_scores_codex":[0.9984908,0.0003494187,0.0003277761,0.0001443294,0.0004852354,0.0002023202],"domain_scores_gemma":[0.9907821,0.003600102,0.003184993,0.0003295185,0.001349684,0.0007536807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007972753,0.0000120896,0.9947048,0.00001713807,0.00001550802,0.0008706204,0.0001696046,0.00005773479,0.0004167756,0.00001485725,0.0001073853,0.003533759],"study_design_scores_gemma":[0.00001165144,0.0001470992,0.9809532,0.00008820317,0.00004931732,0.01446982,0.001718236,0.001172691,0.0007371475,0.0001010219,0.0005330567,0.00001874586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997922,0.0005994899,0.0002211184,0.0001064146,0.00001347674,0.000009955164,0.00006990929,0.000006211499,0.001051561],"genre_scores_gemma":[0.9994843,0.000149923,0.0002129536,0.00002120387,0.00001884926,0.00000225639,0.0000633425,0.000001208187,0.00004594031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003063625,"threshold_uncertainty_score":0.01620215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02593938512829419,"score_gpt":0.3520427412053399,"score_spread":0.3261033560770457,"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."}}