{"id":"W3091860498","doi":"","title":"Rotación ocupacional y calidad del empleo","year":2020,"lang":"es","type":"article","venue":"Desarrollo Económico","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Latin Americans; Quarter (Canadian coin); Wage; Demographic economics; Welfare economics; Geography; Economics; Labour economics; Political science","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":[0.001417921,0.0005154585,0.0004996508,0.002003192,0.0008747056,0.003135678,0.0006479918,0.000541401,0.01923773],"category_scores_gemma":[0.004455779,0.0001963567,0.0005159432,0.00230401,0.001206743,0.001248397,0.001700755,0.0007326064,0.002071141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378793,"about_ca_system_score_gemma":0.0008991752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02649873,"about_ca_topic_score_gemma":0.03221836,"domain_scores_codex":[0.9993398,0.0001719529,0.00003424286,0.0001243125,0.0001659216,0.0001638083],"domain_scores_gemma":[0.9976676,0.000568909,0.0009255765,0.0002744579,0.0003661674,0.0001972437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004549322,0.0002966231,0.5930987,0.0007219032,0.0001317708,0.0009813814,0.01157932,0.001305123,0.001771975,0.01549788,0.01130177,0.3628587],"study_design_scores_gemma":[0.0000359742,0.0001793024,0.8187351,0.0006871927,0.0001042523,0.0006769993,0.01228303,0.001008043,0.0005125905,0.001501574,0.1642348,0.00004097289],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8376504,0.005619399,0.00185345,0.001787127,0.0001627298,0.0001015628,0.003010093,0.0003514966,0.1494637],"genre_scores_gemma":[0.9689392,0.00703038,0.001575168,0.00009878726,0.0002127796,0.00007027212,0.001303629,0.00005447471,0.02071525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02649873,"threshold_uncertainty_score":0.06435663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02647079685746504,"score_gpt":0.2746728990072969,"score_spread":0.2482021021498318,"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."}}