{"id":"W6926465961","doi":"10.25318/9810064401-fra","title":"Population ayant travaillé principalement à temps plein pendant la plupart des semaines durant l’année de référence selon la minorité visible, certaines caractéristiques sociodémographiques et l’année de recensement : Canada, régions géographiques du Canada, provinces et territoires et régions métropolitaines de recensement y compris les parties","year":2024,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Context (archaeology); German population","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.004751227,0.00146971,0.00136664,0.0009856934,0.001553162,0.001366287,0.001112682,0.0005138263,0.00008967903],"category_scores_gemma":[0.00310654,0.001394878,0.0002554179,0.001317443,0.0008839643,0.0005322784,0.0002862251,0.001152872,0.000001500017],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004957253,"about_ca_system_score_gemma":0.01440065,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9982033,"about_ca_topic_score_gemma":0.999983,"domain_scores_codex":[0.9862731,0.003770531,0.002910221,0.001702835,0.003558004,0.001785352],"domain_scores_gemma":[0.9888622,0.005837699,0.001623316,0.0008906584,0.001900118,0.000886065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001353937,0.0004019781,0.1001458,0.001589703,0.0004776235,0.001078367,0.003950208,0.002731693,0.0001628283,0.01790228,0.8659096,0.00551448],"study_design_scores_gemma":[0.0005957453,0.0004135781,0.3434841,0.004034246,0.00122408,0.0003763769,0.02416725,0.01571873,0.0003792781,0.01297849,0.5942061,0.002422074],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3100303,0.003782266,0.009082561,0.01918966,0.00115031,0.001691295,0.6547473,0.0001836134,0.0001427027],"genre_scores_gemma":[0.6678348,0.0299761,0.01052112,0.0007223394,0.0002136367,0.0007362986,0.2892683,0.0001494538,0.0005780149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3654791,"threshold_uncertainty_score":0.9998052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02834475959219064,"score_gpt":0.3307272616301046,"score_spread":0.302382502037914,"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."}}