{"id":"W3006805607","doi":"10.1002/lary.28539","title":"Automatic Recognition of Laryngoscopic Images Using a Deep‐Learning Technique","year":2020,"lang":"en","type":"article","venue":"The Laryngoscope","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Princess Margaret Cancer Centre","funders":"Chengdu Science and Technology Bureau; Fundamental Research Funds for the Central Universities; Sichuan University","keywords":"Medicine; Laryngoscopy; Malignancy; Leukoplakia; Radiology; Internal medicine; Cancer; Surgery; Intubation","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":[0.0002414779,0.0001394717,0.0003190692,0.00006091124,0.0000999098,0.00001469671,0.0001259483,0.00007842427,0.0005341683],"category_scores_gemma":[0.0002815801,0.0001007244,0.00009654603,0.0003883306,0.00009007469,0.0001104485,0.00006302245,0.0003281098,0.00009031907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002055967,"about_ca_system_score_gemma":0.00006415629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007443639,"about_ca_topic_score_gemma":0.000003589151,"domain_scores_codex":[0.9989952,0.0001179631,0.0002772402,0.0001811704,0.0002176371,0.000210773],"domain_scores_gemma":[0.9994447,0.00006930753,0.0001305192,0.0001882219,0.00007734849,0.00008995191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002255204,0.0002422269,0.01407986,0.001735232,0.0002648717,0.00008377819,0.003824102,0.00004998291,0.9138731,0.00004648566,0.0009660208,0.0646088],"study_design_scores_gemma":[0.006323172,0.003660112,0.03350658,0.003176904,0.001890082,0.0004384191,0.004694019,0.06145326,0.8753431,0.001935306,0.006485773,0.00109329],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986268,0.0007526965,0.005254753,0.003319279,0.00003253761,0.0007947789,0.000004231537,0.0002002016,0.003373557],"genre_scores_gemma":[0.9872979,0.0001481131,0.01045962,0.00182683,0.00009897793,0.00003363241,0.0000225688,0.00003736289,0.00007500256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06351551,"threshold_uncertainty_score":0.5848768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03471050291444498,"score_gpt":0.2858266552148498,"score_spread":0.2511161523004048,"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."}}