{"id":"W4377294679","doi":"10.1364/boe.488845","title":"Geometrically accurate real-time volumetric visualization of the middle ear using optical coherence tomography","year":2023,"lang":"en","type":"article","venue":"Biomedical Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Optical coherence tomography; Field of view; Imaging phantom; Tomography; Optics; Middle ear; Computer science; Medical imaging; Visualization; Computer vision; Distortion (music); Artificial intelligence; Physics; Medicine; Anatomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003748385,0.0002419284,0.0003386154,0.00091522,0.000126533,0.00006630376,0.0007689908,0.0002776404,0.0001029198],"category_scores_gemma":[0.0004500555,0.0001984563,0.0002038569,0.01275095,0.0005562322,0.0001364188,0.0002338387,0.0002429536,0.0001031459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004849783,"about_ca_system_score_gemma":0.00005555375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001755614,"about_ca_topic_score_gemma":5.33965e-7,"domain_scores_codex":[0.9975298,0.00005940196,0.0006395694,0.0003352757,0.0008920014,0.0005439658],"domain_scores_gemma":[0.9982342,0.0005075567,0.0001073097,0.0006406616,0.0002034872,0.0003067945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004728283,0.0009486635,0.006061871,0.0008947942,0.000486144,0.0000256299,0.0005831677,0.02001234,0.9326977,0.02380566,0.005613049,0.008823668],"study_design_scores_gemma":[0.000853841,0.0002155153,0.03597535,0.0002997649,0.0002126619,0.00000981108,0.0001261109,0.9327664,0.02559633,0.001328821,0.001766807,0.0008485781],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9510779,0.0001195123,0.04337673,0.00007434085,0.000445494,0.000721213,0.0001191832,0.0009108214,0.00315481],"genre_scores_gemma":[0.9863688,0.0001355131,0.01311171,0.0000145025,0.000108758,0.00006956719,0.00004741168,0.00006281424,0.00008092259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9127541,"threshold_uncertainty_score":0.8092814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03389207036972671,"score_gpt":0.2711496145792119,"score_spread":0.2372575442094852,"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."}}