{"id":"W2984736137","doi":"","title":"Automated Segmentation of Temporal Bone Structures","year":2019,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Facial Nerve Paralysis Treatment and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Segmentation; Computer science; Artificial intelligence; Computer vision","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001697104,0.0002045303,0.0004322921,0.0005732789,0.00007578227,0.00004511897,0.000192929,0.0001641596,0.0001831301],"category_scores_gemma":[0.00001621249,0.0001843367,0.0001821197,0.0005472103,0.00009616609,0.0005269285,0.0001204977,0.0002656342,0.0003044898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001498175,"about_ca_system_score_gemma":0.0001078832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001328324,"about_ca_topic_score_gemma":0.0001412097,"domain_scores_codex":[0.9984534,0.0001426941,0.0002461305,0.0003520967,0.000507167,0.0002985501],"domain_scores_gemma":[0.9990461,0.00004145382,0.0001599325,0.0003874234,0.0001825691,0.0001825063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004297411,0.0001436076,0.9580446,0.0001356343,0.0001913166,0.000171401,0.0001495901,0.00002200166,0.04035326,0.00002784241,0.000001478131,0.000329527],"study_design_scores_gemma":[0.003134623,0.000443491,0.9532874,0.0001170624,0.0001680516,0.0000273602,0.0002347708,0.000003843125,0.04216934,0.00001729226,0.0002314122,0.0001653541],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984776,0.00009020253,0.00002225736,0.0001375965,0.0001079452,0.0005312171,0.00001800027,0.000195606,0.0004196131],"genre_scores_gemma":[0.9869834,0.00002593346,0.0001150385,0.00005622361,0.00002966771,6.291165e-7,0.0001487952,0.00002367378,0.01261665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01219703,"threshold_uncertainty_score":0.7517031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07753078719860411,"score_gpt":0.3633246707627258,"score_spread":0.2857938835641217,"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."}}