{"id":"W2043114588","doi":"10.7202/1016492ar","title":"Maintien en emploi et inégalités de sexe","year":2013,"lang":"fr","type":"article","venue":"Lien social et Politiques","topic":"Social Policy and Reform Studies","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Sociology; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.004676841,0.0002645686,0.0004447541,0.001967676,0.001794602,0.001962382,0.0006343415,0.000704691,0.01024929],"category_scores_gemma":[0.01788854,0.0002478068,0.0004060208,0.002496867,0.002511427,0.001764079,0.002307125,0.001166477,0.0007121687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001130581,"about_ca_system_score_gemma":0.001195886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01889961,"about_ca_topic_score_gemma":0.02491097,"domain_scores_codex":[0.9962877,0.001378514,0.0002422513,0.0005162676,0.0008170706,0.0007580856],"domain_scores_gemma":[0.9890118,0.005538596,0.003179791,0.0008250032,0.0009473541,0.0004975176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003317546,0.00007470883,0.8172176,0.0003122271,0.0001909599,0.0004919884,0.07914254,0.0001033885,0.0005602423,0.02102589,0.002262632,0.07828604],"study_design_scores_gemma":[0.000009101504,0.0001713984,0.9063521,0.0004420428,0.00007913444,0.0007289451,0.05728053,0.0001198978,0.0006609455,0.003725963,0.03040136,0.00002861695],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690452,0.006420117,0.001210977,0.002732723,0.0001136805,0.00002435304,0.0007752696,0.000007987625,0.01966984],"genre_scores_gemma":[0.9908119,0.001916025,0.0002979932,0.0002669078,0.00006476656,0.00003867919,0.0001932616,0.000008634051,0.006401928],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01889961,"threshold_uncertainty_score":0.03757924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04467301382360223,"score_gpt":0.3943331334939037,"score_spread":0.3496601196703015,"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."}}