{"id":"W3083643576","doi":"10.5747/cs.2020.v04.n1.s090","title":"POLÍTICAS PÚBLICAS EFICIENTES PARA O NOVO CORONAVÍRUS NO MUNDO","year":2020,"lang":"en","type":"article","venue":"COLLOQUIUM SOCIALIS","topic":"Healthcare during COVID-19 Pandemic","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Pandemic; Coronavirus disease 2019 (COVID-19); Recession; China; Index (typography); Geography; Government (linguistics); Political science; Coronavirus; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Socioeconomics; Quarantine; Economic growth; Demography; Development economics; Medicine; Economics; Sociology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000441645,0.0003008167,0.0004487724,0.00009603574,0.0004844613,0.000323251,0.00174306,0.000219303,0.0001188128],"category_scores_gemma":[0.001050666,0.0003257673,0.0002016899,0.001150387,0.0001686385,0.0004103256,0.0006773443,0.0003902586,0.002053428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003526357,"about_ca_system_score_gemma":0.0008920181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003274181,"about_ca_topic_score_gemma":0.00003368601,"domain_scores_codex":[0.9968662,0.0002536858,0.0005110933,0.0008371043,0.0006846512,0.0008472831],"domain_scores_gemma":[0.9977795,0.0003947249,0.0001877195,0.0007211507,0.0003066242,0.0006103179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003802351,0.00107448,0.03698139,0.001326263,0.0004887319,0.001363142,0.06169291,0.0001936289,0.04600665,0.5299962,0.2839105,0.03658592],"study_design_scores_gemma":[0.003803574,0.0009786224,0.01217524,0.000124662,0.00007382617,0.00007666843,0.0005380316,0.02617084,0.004517668,0.0037468,0.9456707,0.002123385],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3188979,0.002332872,0.2427312,0.3807063,0.007411647,0.003661519,0.0003168527,0.006874833,0.03706683],"genre_scores_gemma":[0.9680788,0.00003563556,0.005270293,0.02516407,0.0008556785,0.00005892355,0.00001088162,0.00004170673,0.0004839964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6617602,"threshold_uncertainty_score":0.9999194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07164554672837635,"score_gpt":0.3329034102675568,"score_spread":0.2612578635391805,"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."}}