{"id":"W4200044365","doi":"10.1016/j.biosystems.2021.104585","title":"AI in predicting COPD in the Canadian population","year":2021,"lang":"en","type":"article","venue":"Biosystems","topic":"Nursing Diagnosis and Documentation","field":"Nursing","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba; Queen's University","funders":"Canadian Institute for Military and Veteran Health Research; Queen's University; International Business Machines Corporation","keywords":"COPD; Medicine; Population; Medical record; Health care; Primary care; Disease; Psychological intervention; Intensive care medicine; Physical therapy; Family medicine; Internal medicine; Nursing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001764453,0.0008223432,0.0006063299,0.002745065,0.003101637,0.002930374,0.002029922,0.001457795,0.002960443],"category_scores_gemma":[0.009709705,0.0004100619,0.00117898,0.003185076,0.0007251031,0.0007330435,0.001172477,0.002003135,0.0005411761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01463988,"about_ca_system_score_gemma":0.02377288,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.983422,"about_ca_topic_score_gemma":0.9857442,"domain_scores_codex":[0.9986042,0.000153266,0.00008187271,0.0001223365,0.0006080009,0.0004302697],"domain_scores_gemma":[0.9959658,0.0004925474,0.0002978212,0.00008696649,0.002234631,0.0009223056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001703623,0.00006478916,0.9906283,0.00003809419,0.00006292613,0.0000615979,0.0002706103,0.000286014,0.00006914248,0.00018447,0.001801933,0.006361675],"study_design_scores_gemma":[0.00002338613,0.00007735295,0.9897559,0.0001433719,0.000206878,0.0001617722,0.002277157,0.004179806,0.0001144978,0.0003187761,0.002698276,0.00004284238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702216,0.004397368,0.0005033042,0.00232343,0.0002151116,0.00009492614,0.003125158,0.00007517315,0.01904387],"genre_scores_gemma":[0.9947314,0.001269183,0.0006393931,0.0002445561,0.00004193736,0.00001783258,0.0009794565,0.00001258477,0.002063553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01657802,"threshold_uncertainty_score":0.1062202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582851956437412,"score_gpt":0.2932613628588016,"score_spread":0.2774328432944275,"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."}}