{"id":"W3174236985","doi":"10.12688/wellcomeopenres.16953.1","title":"Impact of COVID-19 on non-COVID intensive care unit service utilization, case mix and outcomes: A registry-based analysis from India","year":2021,"lang":"en","type":"preprint","venue":"Wellcome Open Research","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Western Ontario; London Health Sciences Centre; University of Toronto; Western University","funders":"Wellcome Trust","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Medicine; Demography; Disease; Infectious disease (medical specialty)","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":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002433634,0.0006488673,0.002410076,0.00253048,0.0004477032,0.0005517165,0.001202092,0.0008750588,0.001865933],"category_scores_gemma":[0.01171336,0.0005479238,0.0005879522,0.00408352,0.0003208058,0.0001172367,0.002733843,0.002696448,0.00002943161],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002409181,"about_ca_system_score_gemma":0.02636342,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5163547,"about_ca_topic_score_gemma":0.05124904,"domain_scores_codex":[0.993122,0.001474637,0.001060846,0.001758552,0.001672242,0.0009117174],"domain_scores_gemma":[0.9825123,0.003339555,0.0005438018,0.003335017,0.007858962,0.00241034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002956646,0.0003900853,0.9437873,0.008255677,0.003725352,0.01182551,0.02281559,0.002878028,0.0000972818,0.00001251289,0.0023584,0.0008976001],"study_design_scores_gemma":[0.008431089,0.00160299,0.9129255,0.002642915,0.002035311,0.0001523752,0.06363468,0.00506048,0.0003058128,0.0001358788,0.002202323,0.0008706328],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725802,0.0009362202,0.0003438358,0.01807149,0.0001054888,0.004079022,0.003115333,0.00004191676,0.0007264995],"genre_scores_gemma":[0.9821984,0.0003710598,0.0003233184,0.009793309,0.00008672498,0.0001758418,0.006648421,0.00008806216,0.0003148819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4651056,"threshold_uncertainty_score":0.9996972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3981663025747171,"score_gpt":0.5608198227021592,"score_spread":0.1626535201274422,"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."}}