{"id":"W4367156149","doi":"10.1007/978-3-031-31353-0_2","title":"PACTDet - An Artificially Intelligent Approach to Detect Pulmonary Illnesses: Pneumonia, Asthma, COVID-19, and Tuberculosis","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Asthma; Pneumonia; Medicine; Pulmonary tuberculosis; Disease; Decision tree; Preprocessor; Intensive care medicine; Artificial intelligence; Coronavirus disease 2019 (COVID-19); Tuberculosis; Machine learning; Random forest; Computer science; Infectious disease (medical specialty); Immunology; Internal medicine; Pathology","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":[0.000497135,0.0007450404,0.0004331517,0.0008036876,0.0004588541,0.001590924,0.001234553,0.0009527911,0.00947665],"category_scores_gemma":[0.001970031,0.0002779774,0.0006455185,0.0006742557,0.0004589164,0.001097217,0.0008752104,0.001230289,0.003261646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004977757,"about_ca_system_score_gemma":0.0007742436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003702648,"about_ca_topic_score_gemma":0.008254678,"domain_scores_codex":[0.9996971,0.00004986341,0.00002119197,0.00008275023,0.0001310173,0.00001815027],"domain_scores_gemma":[0.9994018,0.0003303797,0.00002200051,0.00005226639,0.0001623452,0.0000311058],"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":[0.0002639901,0.000140063,0.004907524,0.0004625078,0.00008154186,0.0005376053,0.0001627533,0.04487622,0.009712238,0.04895118,0.08891919,0.8009851],"study_design_scores_gemma":[0.00004232338,0.0001806107,0.004406748,0.0002017224,0.0001043094,0.00168729,0.0002051001,0.6861809,0.01908324,0.0786928,0.2091502,0.00006471906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01501811,0.002665576,0.8667616,0.002453529,0.001763874,0.0003452024,0.003970886,0.01015018,0.09687101],"genre_scores_gemma":[0.1129115,0.001961576,0.8240968,0.001318856,0.0003511144,0.0002493966,0.006137035,0.000641177,0.05233254],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00947665,"threshold_uncertainty_score":0.03170258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0906070873394395,"score_gpt":0.3561413153680736,"score_spread":0.2655342280286341,"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."}}