{"id":"W7120815961","doi":"","title":"Severe unemployment in rural Brazil","year":2020,"lang":"pt","type":"article","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Rural Development and Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Unemployment; Probit model; Quarter (Canadian coin); Probit; Rural area; Scale (ratio); Econometric model","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008762464,0.0001630352,0.0003258599,0.0008905517,0.0006846439,0.0005839376,0.0002147188,0.0003259034,0.001118892],"category_scores_gemma":[0.003771371,0.0001970364,0.0003375835,0.0010476,0.0004174037,0.0002690148,0.000980182,0.0002850493,0.0001261529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006930759,"about_ca_system_score_gemma":0.00103663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03853675,"about_ca_topic_score_gemma":0.06546815,"domain_scores_codex":[0.9993918,0.0001904708,0.00006916697,0.00009126932,0.0001138889,0.0001433754],"domain_scores_gemma":[0.9976412,0.0003609082,0.001307986,0.00008899321,0.0002129176,0.0003880748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004368996,0.00002860526,0.9894897,0.00008536639,0.00003223192,0.0002353479,0.002559701,0.0001953758,0.0004541728,0.000508096,0.0002149933,0.006152708],"study_design_scores_gemma":[0.000003109798,0.00007785604,0.9925722,0.00008806332,0.00001948237,0.0005469334,0.004059119,0.0004786552,0.00006720006,0.000282761,0.001796689,0.000007898329],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956887,0.0006389964,0.0002086357,0.0002673703,0.000006455585,0.00002262855,0.0003562946,0.000004974346,0.002805965],"genre_scores_gemma":[0.9994056,0.0002396704,0.00008936068,0.00002307294,0.000004502652,0.000008598541,0.000100364,0.000001056004,0.0001278138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03853675,"threshold_uncertainty_score":0.07662487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01672759592461674,"score_gpt":0.2270238107570651,"score_spread":0.2102962148324484,"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."}}