{"id":"W2046135204","doi":"10.1097/00004728-200603000-00034","title":"High-Resolution Computed Tomography of Temporal Bone","year":2006,"lang":"en","type":"article","venue":"Journal of Computer Assisted Tomography","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Coronal plane; Medicine; Temporal bone; Tomography; Scanner; Visualization; Computed tomography; Volume (thermodynamics); Radiology; Anatomy; Nuclear medicine; Artificial intelligence; Computer science; Physics","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":[0.0002614661,0.0002523505,0.0001239087,0.0008924978,0.0002589782,0.000379763,0.0003059819,0.0006457093,0.004262983],"category_scores_gemma":[0.0008827489,0.000280885,0.0002184226,0.0003865086,0.0003266375,0.0005681498,0.0002556622,0.0004838076,0.0007679592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002370273,"about_ca_system_score_gemma":0.0003176887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00130809,"about_ca_topic_score_gemma":0.001710525,"domain_scores_codex":[0.9998974,0.00002542483,0.00001196669,0.00001232061,0.00003629447,0.00001675652],"domain_scores_gemma":[0.9998266,0.00009249934,0.00001471866,0.00002691938,0.00002292279,0.0000164841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001325352,0.0002132036,0.02228358,0.0007759484,0.0001351788,0.2952419,0.0005486016,0.003775182,0.4803804,0.006598987,0.01195804,0.1767635],"study_design_scores_gemma":[0.0001937714,0.0007045366,0.04479008,0.0002761609,0.0001245416,0.8645508,0.0002904137,0.007419031,0.03647881,0.003334295,0.04175863,0.00007896967],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.781506,0.04428826,0.08113772,0.003777393,0.0005016989,0.0004305872,0.001370826,0.0009653209,0.08602224],"genre_scores_gemma":[0.9394537,0.009208744,0.04168873,0.001230566,0.0002767134,0.00007094303,0.0003929182,0.00009707476,0.007580558],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.004262983,"threshold_uncertainty_score":0.01426113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01550699320003651,"score_gpt":0.24139503035685,"score_spread":0.2258880371568135,"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."}}