{"id":"W3193928955","doi":"10.1016/j.lana.2021.100056","title":"Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study","year":2021,"lang":"en","type":"article","venue":"The Lancet Regional Health - Americas","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Children's Hospital","funders":"","keywords":"Pandemic; Public health; Medicine; Government (linguistics); Confidence interval; Coronavirus disease 2019 (COVID-19); Health care; Elective surgery; Medical emergency; Emergency medicine; Surgery; Nursing; Economics; Internal medicine; Economic growth","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":[],"consensus_categories":[],"category_scores_codex":[0.00115303,0.0001425076,0.0005367207,0.00006624922,0.0002473485,0.00001601733,0.00006990715,0.00006239692,0.00000457252],"category_scores_gemma":[0.0006132911,0.00009548927,0.00003516807,0.0005138926,0.00004880267,0.00003805097,0.00009567669,0.0005558872,7.800674e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004406825,"about_ca_system_score_gemma":0.001606812,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0201319,"about_ca_topic_score_gemma":0.01422427,"domain_scores_codex":[0.9976375,0.0005923592,0.0003918782,0.0003199811,0.0005468502,0.000511407],"domain_scores_gemma":[0.998399,0.0008528743,0.0001704726,0.0002193367,0.0000579628,0.000300365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000399821,0.00005890794,0.9793382,0.0002531108,0.00004573601,0.00005721626,0.01678732,0.000205639,0.000005803725,0.00008812455,0.00014261,0.002617502],"study_design_scores_gemma":[0.003548648,0.0003422119,0.9772511,0.0001037098,0.00002872241,0.0001387381,0.01190842,0.0008591652,9.53634e-7,0.0001952866,0.005516085,0.0001069462],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8299585,0.003027684,0.00002231907,0.1662306,0.00001689508,0.0006584643,0.00002111051,0.00001923029,0.00004524651],"genre_scores_gemma":[0.9753484,0.006936187,0.00001802558,0.01706946,0.0004977477,0.00005240555,0.00001126617,0.00001360033,0.00005293477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1491611,"threshold_uncertainty_score":0.9994151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1606471271842854,"score_gpt":0.4760591699726884,"score_spread":0.315412042788403,"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."}}