{"id":"W2010735893","doi":"10.3917/riges.293.0013","title":"Les fondements démographiques de la main-d'œuvre québécoise de demain","year":2004,"lang":"fr","type":"article","venue":"Gestion","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Political science; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0005327107,0.0002291942,0.0001789196,0.003737005,0.003070739,0.001539675,0.0004032704,0.0003286983,0.01437646],"category_scores_gemma":[0.001431407,0.0001086553,0.0001699398,0.004426543,0.001216649,0.0006881718,0.0007855885,0.0004589267,0.000434658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01771513,"about_ca_system_score_gemma":0.0115957,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9817076,"about_ca_topic_score_gemma":0.9886209,"domain_scores_codex":[0.999713,0.00005647871,0.000009604627,0.00003355392,0.0000710714,0.000116276],"domain_scores_gemma":[0.998702,0.0001716954,0.0001682848,0.00005404595,0.0005954647,0.0003083226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001438014,0.00003839597,0.5628186,0.0002777056,0.0001024743,0.0006561914,0.162405,0.002103998,0.001103868,0.05035662,0.05780027,0.1621931],"study_design_scores_gemma":[0.00000261799,0.00001653892,0.8303979,0.0002190437,0.00001715262,0.0001165769,0.04944826,0.0006216768,0.0001812718,0.001428711,0.1175161,0.00003413931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9161765,0.003493883,0.001349385,0.005154748,0.00005587541,0.0000569314,0.009276246,0.00006676598,0.06436971],"genre_scores_gemma":[0.9627866,0.001048047,0.0006792705,0.0001272619,0.00001104806,0.00004120691,0.001233713,0.00001217856,0.03406073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01829243,"threshold_uncertainty_score":0.1285328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1094745415494696,"score_gpt":0.3980694913722019,"score_spread":0.2885949498227323,"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."}}