{"id":"W812013614","doi":"","title":"Differences in unemployment between males and females in France","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Unemployment; Distribution (mathematics); Economics; Welfare; Demographic economics; Unemployment rate; Duration (music); Quarter (Canadian coin); Labour economics; Welfare state; Econometrics; Demography; Mathematics; Sociology; Geography; Political science; Economic growth","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":[0.0007589498,0.0001792068,0.0002737201,0.001021599,0.0004883075,0.0006368297,0.000174584,0.0003360669,0.003558708],"category_scores_gemma":[0.001107733,0.00008464509,0.0003101619,0.0005064493,0.0002391525,0.0002417944,0.0004361013,0.0002233682,0.0004190876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009106502,"about_ca_system_score_gemma":0.0002926819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02491608,"about_ca_topic_score_gemma":0.02886197,"domain_scores_codex":[0.9993545,0.0001741679,0.00002850774,0.0001442233,0.0001245539,0.000173939],"domain_scores_gemma":[0.9995313,0.0001755102,0.0001418204,0.00001830905,0.00006908353,0.00006406058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00044686,0.0001037143,0.9006369,0.00007887427,0.0001405992,0.0003479258,0.009617288,0.00123048,0.002045412,0.006413198,0.00350771,0.075431],"study_design_scores_gemma":[0.00000368956,0.00008349567,0.9930708,0.0000200852,0.000008117593,0.0001551833,0.001198605,0.0003807613,0.00009641688,0.0002236298,0.0047489,0.00001025976],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930274,0.001457396,0.000354515,0.0003110251,0.00002352065,0.000006340811,0.0005955857,0.000009197196,0.004214935],"genre_scores_gemma":[0.9964759,0.0004374832,0.0001556499,0.0000532385,0.00002732091,0.00000870754,0.0003800681,0.000004883462,0.002456791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02491608,"threshold_uncertainty_score":0.04954213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03983513852113658,"score_gpt":0.2543698460444466,"score_spread":0.21453470752331,"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."}}