{"id":"W2114329998","doi":"10.3917/riges.264.0042","title":"Retraite anticipée ou retraite normale?","year":2001,"lang":"fr","type":"article","venue":"Gestion","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts (Québec)","funders":"","keywords":"Political science; Humanities; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001441327,0.0002211376,0.0002267976,0.00006337138,0.0005266276,0.000122377,0.000318502,0.0003604224,0.002496513],"category_scores_gemma":[0.0004534168,0.0002413751,0.0001532398,0.0006737476,0.0007105196,0.0005245216,0.00007246112,0.0003074589,0.001109999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004113018,"about_ca_system_score_gemma":0.00009170849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003569333,"about_ca_topic_score_gemma":0.002561333,"domain_scores_codex":[0.9972608,0.0004195683,0.0004207108,0.0004519839,0.0006961851,0.0007507498],"domain_scores_gemma":[0.9989751,0.00009647186,0.0001463597,0.0003803117,0.000131716,0.0002700393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009039575,0.0008623058,0.4955963,0.0002184169,0.00007283605,0.00004620965,0.01874522,0.0001428844,0.0005648303,0.0723307,0.02299221,0.3883377],"study_design_scores_gemma":[0.0003851883,0.0002466772,0.5270731,0.0002606192,0.0001024784,0.00001053814,0.001285961,0.0003957659,0.00008239858,0.008321146,0.4614386,0.0003975266],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8033134,0.002096173,0.0003008443,0.116027,0.004629527,0.0004372627,0.00001736147,0.0001287902,0.07304965],"genre_scores_gemma":[0.9395708,0.003380712,0.0002998479,0.0004520208,0.001393116,0.00001562652,0.00002327076,0.00002050897,0.05484407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4384464,"threshold_uncertainty_score":0.9996678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2078947297649616,"score_gpt":0.4030243442525637,"score_spread":0.1951296144876021,"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."}}