{"id":"W1749945614","doi":"","title":"Optical Coherence Tomography for Clinical Otology","year":2015,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Eardrum; Optical coherence tomography; Middle ear; Malleus; Stapes; Optical tomography; Otology; Optics; Tomography; Interferometry; Medical imaging; Biomedical engineering; Computer science; Materials science; Acoustics; Physics; Artificial intelligence; Engineering; Medicine; Radiology; Surgery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001610956,0.00073578,0.000726447,0.00240352,0.000440676,0.001738306,0.0006354325,0.001801038,0.03782999],"category_scores_gemma":[0.005452982,0.0002171969,0.0005481871,0.001619319,0.001077155,0.001360665,0.001264255,0.002668523,0.02096848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001210342,"about_ca_system_score_gemma":0.001740974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001028246,"about_ca_topic_score_gemma":0.001084435,"domain_scores_codex":[0.9989564,0.0002387753,0.0001014069,0.0001861198,0.0004419083,0.00007521843],"domain_scores_gemma":[0.9974108,0.00061486,0.0003222636,0.0003065112,0.001093853,0.0002516548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001679481,0.00006739527,0.001457899,0.0009752776,0.00006065797,0.0009178444,0.00007710925,0.0001887591,0.00585962,0.01283005,0.224369,0.7530285],"study_design_scores_gemma":[0.0000841626,0.0001091225,0.00497612,0.00151028,0.00006167206,0.009716984,0.00009044869,0.0006245116,0.002191581,0.01582616,0.9647571,0.00005176279],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.006592721,0.6177291,0.07997861,0.07488949,0.01385314,0.0006094691,0.003346042,0.004120554,0.198881],"genre_scores_gemma":[0.1505527,0.4565761,0.1265265,0.05372769,0.03266223,0.002086727,0.00688647,0.00156422,0.1694173],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03782999,"threshold_uncertainty_score":0.126554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06112656044554996,"score_gpt":0.3103920013891468,"score_spread":0.2492654409435968,"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."}}