{"id":"W7104436226","doi":"10.71781/12893","title":"Déterminants du revenu des familles d'ici et d'ailleurs à Montréal, Toronto et Vancouver","year":2001,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Social Sciences and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Inequality; Population; Agency (philosophy)","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":[0.0008449902,0.0002586858,0.0004227269,0.00184885,0.005923382,0.003411472,0.001501889,0.0005837646,0.01088255],"category_scores_gemma":[0.005764268,0.0004124009,0.000343605,0.003993371,0.001798207,0.0006587298,0.00205426,0.001279794,0.0003696055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03341222,"about_ca_system_score_gemma":0.03741238,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947068,"about_ca_topic_score_gemma":0.9983013,"domain_scores_codex":[0.9988066,0.0002036739,0.00004268793,0.0001486769,0.000214119,0.000584189],"domain_scores_gemma":[0.9921924,0.001006599,0.001061459,0.000194325,0.002498076,0.003047158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001654025,0.0000636091,0.9244997,0.0001061933,0.00008038613,0.0004273691,0.03375692,0.0004264009,0.0003629875,0.007542559,0.01639826,0.01617026],"study_design_scores_gemma":[0.00000881394,0.00001637656,0.9684475,0.00008008254,0.0000175587,0.00004454277,0.02413129,0.0001633185,0.00008154001,0.000110536,0.006879621,0.00001877573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779089,0.001037907,0.0001706871,0.003656397,0.00003000271,0.00003875042,0.002919846,0.00002567522,0.01421183],"genre_scores_gemma":[0.9898694,0.0003772082,0.0001284867,0.00008111363,0.000007363281,0.00002084706,0.0004434747,0.000007940237,0.00906418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03341222,"threshold_uncertainty_score":0.2424238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01088670417636825,"score_gpt":0.2299599844128539,"score_spread":0.2190732802364857,"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."}}