{"id":"W2590547535","doi":"10.1017/s0022215116002607","title":"Combine MR and CT imaging in cholesteatoma","year":2016,"lang":"en","type":"article","venue":"The Journal of Laryngology & Otology","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Content (measure theory); Cholesteatoma; Computer science; Medicine; Radiology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006256608,0.00009202518,0.0003640249,0.000184168,0.00003219279,0.000002047173,0.0001271475,0.0000469026,0.0001153196],"category_scores_gemma":[0.0001624849,0.0000448858,0.00004859737,0.00008027157,0.0003556332,0.00007679273,0.00004498524,0.0002616033,0.0000157995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002201749,"about_ca_system_score_gemma":0.00005964802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003025996,"about_ca_topic_score_gemma":0.00007532429,"domain_scores_codex":[0.999078,0.0002017231,0.0003322142,0.00008132447,0.00007998772,0.0002267326],"domain_scores_gemma":[0.9992523,0.0002986141,0.0001663353,0.0001567206,0.00005784851,0.00006814477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000522307,0.0001140826,0.957997,0.00001265,0.00006290902,0.001264301,0.0003064941,3.663019e-7,0.02188867,0.0005640249,0.001558845,0.01570837],"study_design_scores_gemma":[0.007084138,0.0006937766,0.9348088,0.0000976411,0.0001477813,0.04677939,0.0003613239,0.0000130066,0.001572332,0.00241969,0.005936199,0.0000859178],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9431115,0.001920256,0.00006748267,0.05384785,0.0001226523,0.00009072823,5.234309e-7,0.000006511975,0.0008325303],"genre_scores_gemma":[0.9959318,0.0008682134,0.0000650978,0.002888233,0.00005743491,0.000001169475,2.686271e-7,0.000009627703,0.0001781238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05282037,"threshold_uncertainty_score":0.183039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008233983040142766,"score_gpt":0.2636952857680973,"score_spread":0.2554613027279545,"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."}}