{"id":"W4394878648","doi":"10.51161/conasf2024/32214","title":"PROPORÇÃO ENTRE INTERNAÇÕES E ÓBITOS POR INFARTO AGUDO DO MIOCÁRDIO NO PERÍODO DE 2019 A 2023 NO RIO GRANDE DO SUL","year":2024,"lang":"pt","type":"article","venue":"","topic":"Healthcare during COVID-19 Pandemic","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Medicine","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002261256,0.001085143,0.001049862,0.0008567362,0.0004143135,0.002718659,0.003059404,0.0007326896,0.002461919],"category_scores_gemma":[0.0007559319,0.0009652479,0.0006956951,0.001523676,0.0002566263,0.001307864,0.001754197,0.001869624,0.03190603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00126717,"about_ca_system_score_gemma":0.0034198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005050197,"about_ca_topic_score_gemma":0.0008170296,"domain_scores_codex":[0.9912462,0.0007426739,0.001578131,0.00255436,0.001488843,0.002389764],"domain_scores_gemma":[0.9948245,0.0007963155,0.0002842419,0.002245875,0.0005837826,0.001265236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003821972,0.0006097569,0.05332589,0.006641109,0.0009190139,0.004723048,0.03600534,0.0001637362,0.004302454,0.006156042,0.8155456,0.07122587],"study_design_scores_gemma":[0.002576023,0.00143116,0.00664775,0.006973429,0.0002070686,0.001308128,0.000916556,0.1164118,0.001663693,0.00109676,0.8577222,0.003045479],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5256007,0.05167602,0.1953011,0.06522551,0.06772027,0.01046703,0.0008394716,0.009138368,0.07403158],"genre_scores_gemma":[0.7679992,0.001650548,0.004121122,0.005190155,0.002913583,0.0001476737,0.00003562872,0.0002084949,0.2177336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2423985,"threshold_uncertainty_score":0.9992798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01752250470657035,"score_gpt":0.3053644166779902,"score_spread":0.2878419119714198,"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."}}