{"id":"W4223963350","doi":"10.12961/aprl.2022.25.02.06","title":"Datos y evidencias del teletrabajo, antes y durante la pandemia por COVID-19","year":2022,"lang":"es","type":"article","venue":"Archivos de Prevención de Riesgos Laborales","topic":"Labor Law and Work Dynamics","field":"Social Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Pandemic; Coronavirus disease 2019 (COVID-19); Work (physics); Nothing; Latin Americans; Demographic economics; Political science; Economic growth; Economics; Geography; Development economics; Engineering; Law; Medicine","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","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004947959,0.0007122295,0.000865938,0.000326697,0.003910281,0.0005394669,0.002337967,0.0003490629,0.001120473],"category_scores_gemma":[0.003561768,0.0007602106,0.000407701,0.002137787,0.001764141,0.0006531603,0.001104586,0.001725396,0.00006190852],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342711,"about_ca_system_score_gemma":0.007948896,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006738616,"about_ca_topic_score_gemma":0.004573253,"domain_scores_codex":[0.9894009,0.005063318,0.0009781793,0.001139178,0.001470572,0.001947813],"domain_scores_gemma":[0.9932736,0.003688622,0.0006043246,0.0009923386,0.0002019192,0.001239183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005631635,0.0009051177,0.5391745,0.0007503253,0.0004858004,0.001264078,0.06003357,0.001752275,0.002365306,0.3697004,0.01458917,0.008416247],"study_design_scores_gemma":[0.002222419,0.0005691132,0.07134148,0.0004349521,0.0005800033,0.0003787366,0.02045446,0.003409895,0.0001962252,0.07832864,0.8199231,0.002160982],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.961746,0.005196848,0.001774155,0.01938726,0.0005455663,0.001336768,0.002878896,0.0005669201,0.006567627],"genre_scores_gemma":[0.9789089,0.008959034,0.002602454,0.004711878,0.0005517107,0.0003514975,0.0001373151,0.0001293527,0.003647883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8053339,"threshold_uncertainty_score":0.9998756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.017801953428059,"score_gpt":0.3270347421514747,"score_spread":0.3092327887234156,"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."}}