{"id":"W4403070547","doi":"10.1093/clinchem/hvae106.497","title":"B-136 From Result to Response: The Development of Laboratory-Based Scoring Models to Predict COVID-19 Patient Outcomes","year":2024,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York Central Hospital; Mount Sinai Hospital; William Osler Health System; Simon Fraser University; University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Medicine; Virology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.007229525,0.0009730588,0.0006909236,0.002236061,0.0003711653,0.001978834,0.0009978799,0.0006156382,0.002716752],"category_scores_gemma":[0.02258538,0.0002683541,0.001089598,0.001248731,0.0003424508,0.0008016095,0.001079117,0.001146509,0.000895576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001591926,"about_ca_system_score_gemma":0.002167574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02970807,"about_ca_topic_score_gemma":0.02518055,"domain_scores_codex":[0.9974189,0.001356448,0.0002622763,0.0003115556,0.0004382787,0.0002125348],"domain_scores_gemma":[0.9870377,0.007114007,0.002256291,0.0005458375,0.002428527,0.0006177188],"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":[0.0009107715,0.0003572994,0.8872873,0.0001326159,0.0005210123,0.00006755334,0.0001421032,0.02391758,0.0004187234,0.0006269819,0.006355704,0.07926248],"study_design_scores_gemma":[0.0001850309,0.001141505,0.3350833,0.0001658608,0.0003361428,0.0002320955,0.0003345306,0.6550023,0.0008261409,0.003021343,0.003592705,0.00007909217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8634657,0.001369361,0.109753,0.002791404,0.0002492953,0.00101624,0.01035577,0.001431639,0.00956767],"genre_scores_gemma":[0.973668,0.0001992965,0.02130336,0.0001894182,0.00005841837,0.0003177868,0.003295371,0.00003455066,0.0009337735],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02970807,"threshold_uncertainty_score":0.05907035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1010909474756419,"score_gpt":0.4143294170616783,"score_spread":0.3132384695860363,"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."}}