{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007321952,0.0002105309,0.0002201116,0.001193773,0.0003434989,0.0008441524,0.0004162061,0.0004471494,0.003118895],"category_scores_gemma":[0.003664369,0.0001885084,0.0003540252,0.001676017,0.0004931805,0.0005645254,0.0009601937,0.0005068033,0.0004427017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109884,"about_ca_system_score_gemma":0.001302575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06802559,"about_ca_topic_score_gemma":0.1223363,"domain_scores_codex":[0.99943,0.0001213888,0.00006604315,0.000119373,0.0001412874,0.0001219074],"domain_scores_gemma":[0.9970767,0.0005332497,0.001364841,0.0001707881,0.0005451966,0.000309168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002042687,0.00001717417,0.9780985,0.0002809691,0.00007006632,0.0002155716,0.003324767,0.0001518917,0.0006708452,0.0006085108,0.002392725,0.0139647],"study_design_scores_gemma":[0.000003010309,0.0000457749,0.9909412,0.0001277983,0.00004142751,0.0002167153,0.003232248,0.0002084882,0.0002089588,0.0001136499,0.004850537,0.00001013057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773607,0.002137138,0.000558404,0.001285721,0.0000387386,0.00004970596,0.01087846,0.00003968858,0.007651517],"genre_scores_gemma":[0.9933703,0.00129443,0.0004225815,0.0001481772,0.00003808367,0.00004749331,0.002212619,0.00001103369,0.002455313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06802559,"threshold_uncertainty_score":0.1352593,"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."}}