{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001709189,0.0002858592,0.0003960174,0.001720495,0.000629056,0.0004215082,0.0009877743,0.0001742555,0.000009787124],"category_scores_gemma":[0.0004358435,0.0002856667,0.00005284494,0.0007327634,0.0008845024,0.001821497,0.001507648,0.0004742028,0.00007412559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000412343,"about_ca_system_score_gemma":0.0008065447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001471816,"about_ca_topic_score_gemma":0.00006484219,"domain_scores_codex":[0.9979003,0.00005402883,0.0007721703,0.0004487241,0.0005477772,0.000277002],"domain_scores_gemma":[0.9964711,0.0004857941,0.0002174739,0.001951073,0.0003409109,0.0005336552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005427703,0.0001862874,0.0003281414,0.0007766404,0.00003921485,0.000006499012,0.01402473,0.003768226,0.00008437435,0.05468837,0.001658534,0.9243847],"study_design_scores_gemma":[0.0003857383,0.0003718552,0.008055337,0.0008071865,0.00006344231,0.0001971806,0.0004555405,0.3363482,0.00004474941,0.004758116,0.6476825,0.0008301156],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008248879,0.002173876,0.6460655,0.1431828,0.002245375,0.01168991,0.0004544576,0.002022758,0.1839165],"genre_scores_gemma":[0.4672411,0.02944468,0.2913852,0.2019421,0.0005664389,0.001178541,0.002270923,0.0002824909,0.005688554],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9235546,"threshold_uncertainty_score":0.9999595,"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."}}