{"id":"W4392000329","doi":"10.2196/54388","title":"Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania","year":2024,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Respiratory and Cough-Related Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"COPD; Tanzania; Medicine; Asthma; Protocol (science); User Friendly; Computer science; Intensive care medicine; Alternative medicine; Pathology; Immunology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01201766,0.001289719,0.001111063,0.000656722,0.001611575,0.0009068175,0.001475072,0.001649854,0.01417448],"category_scores_gemma":[0.01516124,0.000864785,0.001456919,0.0004190433,0.001377886,0.0006609818,0.001146704,0.00189923,0.003619509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001636351,"about_ca_system_score_gemma":0.005516246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002557522,"about_ca_topic_score_gemma":0.004437229,"domain_scores_codex":[0.9965979,0.001847259,0.0003823344,0.0004144297,0.0005086841,0.0002493552],"domain_scores_gemma":[0.9921266,0.002050415,0.0007214979,0.00106989,0.00345996,0.0005716902],"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":[0.1370483,0.1545498,0.04818573,0.02052209,0.001392487,0.00328948,0.01031823,0.02616264,0.1546067,0.0101878,0.04158453,0.3921524],"study_design_scores_gemma":[0.08026148,0.4346365,0.1505001,0.007254867,0.002049481,0.001891864,0.007758972,0.02427697,0.08983057,0.01060443,0.1899838,0.0009509841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.09702256,0.0003470798,0.02859391,0.0003653183,0.0002753682,0.8681778,0.002096215,0.0002257172,0.002895995],"genre_scores_gemma":[0.0340212,0.0002190118,0.03362565,0.0004305,0.00004257154,0.9292188,0.0007875462,0.00002263685,0.001632136],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.01417448,"threshold_uncertainty_score":0.06355619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2467230756456482,"score_gpt":0.5509908530929386,"score_spread":0.3042677774472904,"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."}}