{"id":"W3177880373","doi":"10.2298/stnv2101017j","title":"COVID-19 and excess mortality: Was it possible to lower the number of deaths in Slovenia?","year":2021,"lang":"en","type":"article","venue":"Stanovnistvo","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Javna Agencija za Raziskovalno Dejavnost RS","keywords":"Excess mortality; Coronavirus disease 2019 (COVID-19); Demography; Quarter (Canadian coin); Population; Mortality rate; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; 2019-20 coronavirus outbreak; Geography; Disease; Virology; Internal medicine; Infectious disease (medical specialty); Outbreak","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005057635,0.0001456249,0.0003772978,0.00007104042,0.000082219,0.00003059629,0.00009490412,0.00009782799,0.0008940043],"category_scores_gemma":[0.001437518,0.0001095133,0.00006400317,0.0005358787,0.00009950911,0.00005654292,0.0001033365,0.0002112899,0.00002354004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002666256,"about_ca_system_score_gemma":0.002487068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002865701,"about_ca_topic_score_gemma":0.005312185,"domain_scores_codex":[0.9985134,0.00008445088,0.0003710186,0.0003164643,0.0003755144,0.0003391739],"domain_scores_gemma":[0.9984033,0.0002841308,0.0000680496,0.0005257783,0.0001513966,0.0005673268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000863347,0.0005364416,0.9491092,0.002663259,0.0001428991,0.002063917,0.009947493,0.00001880217,0.004738387,0.009511991,0.01457875,0.005825501],"study_design_scores_gemma":[0.004107141,0.0004248654,0.5897603,0.0006219344,0.0001699368,0.0003348916,0.00391934,0.00004559885,0.005519719,0.005885017,0.3887728,0.0004384349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9309586,0.0004338891,0.0001900072,0.05872658,0.0001775731,0.0003903162,0.00007184616,0.00002372199,0.009027488],"genre_scores_gemma":[0.9698879,0.0001399331,0.0001929502,0.02680378,0.00009154266,0.0000147098,0.00001218364,0.00001942211,0.002837536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3741941,"threshold_uncertainty_score":0.9788721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09341522389051943,"score_gpt":0.4580549199574199,"score_spread":0.3646396960669004,"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."}}