{"id":"W3055184672","doi":"10.1002/lary.29009","title":"Predicting the Premorbid Shape of a Diseased Mandible","year":2020,"lang":"en","type":"article","venue":"The Laryngoscope","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stornoway Diamond (Canada); University of British Columbia","funders":"Michael Smith Health Research BC","keywords":"Mandible (arthropod mouthpart); Preprocessor; Condyle; Hausdorff distance; Surgical planning; Segmentation; Orthodontics; Artificial intelligence; Computer science; Mathematics; Medicine; Radiology; Biology; Genus","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009315565,0.0004228099,0.0002297221,0.0009064983,0.0001570307,0.0005598083,0.000533035,0.0006249302,0.0008757038],"category_scores_gemma":[0.003815277,0.0004608382,0.0005229985,0.0002254404,0.0004689211,0.0004426275,0.00040767,0.0003629307,0.0003674995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004183893,"about_ca_system_score_gemma":0.0006144224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002164635,"about_ca_topic_score_gemma":0.002592135,"domain_scores_codex":[0.9996674,0.00005035077,0.00003229451,0.00007393443,0.0001591169,0.00001687865],"domain_scores_gemma":[0.9988501,0.0004790097,0.0002837053,0.0002190905,0.0001305703,0.0000373855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005709362,0.0001199543,0.4427363,0.000150674,0.00009949517,0.00156309,0.0003942277,0.2880079,0.08857176,0.0006709558,0.0006565566,0.176458],"study_design_scores_gemma":[0.00001772185,0.0005224699,0.1530742,0.00004815291,0.00006881652,0.01041386,0.0002923773,0.7940838,0.03898725,0.0007839463,0.001644579,0.00006268206],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.926945,0.0002209943,0.07139546,0.00009577611,0.00001212175,0.00003828011,0.0001646673,0.0002970759,0.0008305582],"genre_scores_gemma":[0.9735339,0.0001315018,0.02578989,0.00001305268,0.000005589753,0.000012206,0.0001986331,0.00002734954,0.0002879738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002164635,"threshold_uncertainty_score":0.004926622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024046639663001,"score_gpt":0.2547225071116642,"score_spread":0.2344820407150342,"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."}}