{"id":"W2470165734","doi":"10.7202/1035955ar","title":"Vivre et travailler plus longtemps au Canada : la réalité des baby-boomers","year":2016,"lang":"fr","type":"article","venue":"Cahiers québécois de démographie","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":9,"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":[0.0008858349,0.0001955799,0.0002918549,0.0006653646,0.006234242,0.003068361,0.0009949745,0.0007276284,0.007412109],"category_scores_gemma":[0.00263583,0.0002446404,0.0003001163,0.001696788,0.001786869,0.001273097,0.001894161,0.001878241,0.0003188958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03146781,"about_ca_system_score_gemma":0.0747585,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9892859,"about_ca_topic_score_gemma":0.9948113,"domain_scores_codex":[0.9990277,0.0001212989,0.00001473397,0.00006992197,0.0002206333,0.0005455965],"domain_scores_gemma":[0.998201,0.000114591,0.000215643,0.00003813076,0.0004712054,0.0009593733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003549832,0.0001230271,0.7238299,0.0003275499,0.0001296834,0.001196749,0.09001771,0.0006423215,0.001027707,0.03818646,0.04235914,0.1018049],"study_design_scores_gemma":[0.00003187121,0.0001000504,0.7401834,0.0006492282,0.000106553,0.0002865432,0.1443182,0.0007433761,0.0004468565,0.002014474,0.1110127,0.0001068054],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9363497,0.004978471,0.0003397116,0.03602388,0.0001398719,0.00003809035,0.001926045,0.00002381411,0.02018037],"genre_scores_gemma":[0.9846594,0.004398632,0.0002217995,0.001939125,0.00003011105,0.00001841979,0.0004216517,0.00001727782,0.008293541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03146781,"threshold_uncertainty_score":0.228316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05969598154331431,"score_gpt":0.3240190377051147,"score_spread":0.2643230561618004,"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."}}