{"id":"W4382360308","doi":"10.54871/cl4c400o","title":"Análisis de la influencia de la institucionalización del género en la transversalización del género en las respuestas estatales a la pandemia por COVID-19","year":2023,"lang":"es","type":"article","venue":"Tramas y Redes","topic":"Gender, Health, and Social Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Network for Business Sustainability","funders":"","keywords":"Humanities; Political science; Coronavirus disease 2019 (COVID-19); Art; 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":[0.009330768,0.0003584953,0.00050821,0.00220675,0.001811833,0.002184266,0.000724592,0.0005154384,0.008643414],"category_scores_gemma":[0.02119564,0.0003404818,0.001152409,0.003021425,0.001423587,0.001514589,0.00324052,0.001016145,0.0003317745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003768434,"about_ca_system_score_gemma":0.006615493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05957679,"about_ca_topic_score_gemma":0.08430704,"domain_scores_codex":[0.9932522,0.004062571,0.0004396356,0.0004396293,0.0008503171,0.0009556736],"domain_scores_gemma":[0.9820623,0.006919173,0.004859345,0.001330836,0.003854439,0.0009738789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004066462,0.00009644961,0.8915591,0.0009664707,0.0008092588,0.0003418447,0.04890584,0.000296549,0.0007319205,0.009230694,0.002403575,0.04425169],"study_design_scores_gemma":[0.00001849254,0.0002060154,0.9276743,0.0009064625,0.0004619261,0.0001964928,0.05036412,0.0004958491,0.0005615159,0.001907905,0.01717324,0.00003369237],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718749,0.003676016,0.003262924,0.002820517,0.00008773226,0.0003627402,0.002589214,0.00002382313,0.01530212],"genre_scores_gemma":[0.9934037,0.001157476,0.001101918,0.0002541212,0.00002685339,0.0003286356,0.0005496949,0.00001194782,0.003165588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05957679,"threshold_uncertainty_score":0.11846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04844013455410925,"score_gpt":0.4167246883069673,"score_spread":0.3682845537528581,"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."}}