{"id":"W637474136","doi":"","title":"Le vieillissement de la population en Chine et au Canada : deux voies pour une même destination?","year":2002,"lang":"fr","type":"book","venue":"UMI Dissertation Services eBooks","topic":"Aging, Elder Care, and Social Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Political science","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":[0.0007461471,0.0004169772,0.0004125269,0.001394139,0.008737117,0.006510228,0.001210973,0.001563014,0.01098434],"category_scores_gemma":[0.0019615,0.0002698255,0.0006140338,0.004121633,0.00385501,0.002771668,0.001645436,0.002718183,0.0006332841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04782436,"about_ca_system_score_gemma":0.1469361,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955901,"about_ca_topic_score_gemma":0.9984328,"domain_scores_codex":[0.999371,0.00004376082,0.00001431454,0.00004249339,0.0001700736,0.0003583437],"domain_scores_gemma":[0.9990608,0.00004729095,0.00004029892,0.00001548538,0.0004964275,0.0003397465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002052007,0.0001138061,0.06452908,0.0006076922,0.0001103228,0.001837541,0.1048747,0.0009857203,0.0009663677,0.2365067,0.2639338,0.325329],"study_design_scores_gemma":[0.00001837353,0.00003864505,0.07411572,0.0009411965,0.00008117197,0.0006418822,0.1790576,0.0003915736,0.0003807989,0.009771167,0.7344378,0.0001241574],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2257075,0.1102452,0.001826121,0.3707991,0.004825466,0.00008349156,0.002862206,0.0001497779,0.2835011],"genre_scores_gemma":[0.5510665,0.07218558,0.002881782,0.01361106,0.0005576013,0.00008309934,0.0009221064,0.0002449912,0.3584473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04782436,"threshold_uncertainty_score":0.3469917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01474455265069039,"score_gpt":0.3512780216488624,"score_spread":0.336533468998172,"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."}}