{"id":"W2973387681","doi":"10.1002/lary.28292","title":"Otoscopic diagnosis using computer vision: An automated machine learning approach","year":2019,"lang":"en","type":"article","venue":"The Laryngoscope","topic":"Ear Surgery and Otitis Media","field":"Medicine","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medical diagnosis; Artificial intelligence; Computer science; Machine learning; Preprocessor; Triage; Upload; Otorhinolaryngology; Referral; Medicine; Family medicine; Medical emergency; Pathology; World Wide Web; Surgery","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":[0.001575283,0.0008758343,0.0005786524,0.003009109,0.0005865588,0.00136808,0.001009301,0.00131632,0.00129661],"category_scores_gemma":[0.005354835,0.0002795194,0.0007301992,0.001174569,0.0006435644,0.001115915,0.0006551145,0.000897188,0.0008373021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113327,"about_ca_system_score_gemma":0.00120155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004725471,"about_ca_topic_score_gemma":0.005043356,"domain_scores_codex":[0.9986057,0.0003309472,0.0000927057,0.0003720252,0.000494187,0.0001044423],"domain_scores_gemma":[0.9976215,0.00100425,0.0002815,0.0001853645,0.0008495541,0.00005778278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000194721,0.0005778801,0.01326836,0.0002171301,0.0001684073,0.0002555457,0.0001317148,0.09942299,0.03000115,0.002175103,0.004226187,0.8493609],"study_design_scores_gemma":[0.0000244019,0.0002270477,0.006889925,0.00005625745,0.00004813047,0.000375057,0.00006027306,0.967689,0.01786579,0.003789871,0.002935796,0.00003835635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.100756,0.0007455114,0.8909982,0.0005509124,0.0001081506,0.0002544453,0.0002052907,0.002984346,0.003397265],"genre_scores_gemma":[0.4766358,0.0003225413,0.5199843,0.000327491,0.0001415226,0.0001646861,0.0003734248,0.00007713489,0.001973133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004725471,"threshold_uncertainty_score":0.009395897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02141184903193415,"score_gpt":0.2971068505075384,"score_spread":0.2756950014756042,"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."}}