{"id":"W3084585617","doi":"10.1503/cmaj.200756","title":"Development of a framework for critical care resource allocation for the COVID-19 pandemic in Saskatchewan","year":2020,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Disaster Response and Management","field":"Health Professions","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Saskatchewan Health; Saskatchewan Health Authority","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Resource allocation; 2019-20 coronavirus outbreak; Health care rationing; Process (computing); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Key (lock); Computer science; Resource (disambiguation); Coronavirus; Health care; Data science; Medicine; Economic growth; Virology; Disease; Computer security; Infectious disease (medical specialty); Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003009963,0.00007277651,0.0001671555,0.0000775033,0.0006146911,0.00001484418,0.0002317261,0.0002853702,0.0004069191],"category_scores_gemma":[0.02024394,0.00005758127,0.00005943952,0.00015224,0.00002477229,0.00003605276,0.00002454194,0.0006422824,0.00001182675],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001512422,"about_ca_system_score_gemma":0.009848207,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005334997,"about_ca_topic_score_gemma":0.09919623,"domain_scores_codex":[0.9980405,0.00032953,0.0005943102,0.0001227193,0.0005060543,0.0004068657],"domain_scores_gemma":[0.9949448,0.003492085,0.0001942292,0.00006968341,0.0002346944,0.001064574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004486877,0.00004408246,0.04981382,0.001133129,0.0001801037,0.00002019561,0.5357111,0.00005219005,0.00001329089,0.02079707,0.2581148,0.1336716],"study_design_scores_gemma":[0.0007805001,0.00003012248,0.001359576,0.00008952899,0.000019126,0.000001058693,0.1792363,0.0001924048,8.161051e-7,0.0008743261,0.8173594,0.00005682193],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0323737,0.0003966187,0.4649993,0.4987643,0.0007450141,0.001959247,0.0001001569,0.00002754553,0.0006341223],"genre_scores_gemma":[0.769789,0.00002097895,0.01371952,0.2140101,0.001497424,0.0005423276,0.0000418828,0.00002873156,0.0003500236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7374153,"threshold_uncertainty_score":0.995765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08963845902504593,"score_gpt":0.4226358457770582,"score_spread":0.3329973867520123,"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."}}