{"id":"W6945421752","doi":"10.25318/9810031801-fra","title":"Catégorie d'admission selon la période d'immigration et l'expérience avant l'admission : Canada, provinces et territoires, régions métropolitaines de recensement et agglomérations de recensement y compris les parties","year":2022,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Context (archaeology); China; Earth Summit","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":[0.001100256,0.001182948,0.001251656,0.00583812,0.001696611,0.002739709,0.002231049,0.001154182,0.02725112],"category_scores_gemma":[0.009491215,0.0006872814,0.001266244,0.01787588,0.0005180229,0.0009645958,0.001540072,0.002113082,0.01218798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01532289,"about_ca_system_score_gemma":0.03632474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9737178,"about_ca_topic_score_gemma":0.9822107,"domain_scores_codex":[0.9986292,0.0000849542,0.0001708077,0.0002233337,0.0004510238,0.000440596],"domain_scores_gemma":[0.9925315,0.0008721661,0.0006028093,0.0004256096,0.004880325,0.0006876143],"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":[0.00009466795,0.00002567592,0.01890215,0.0006213923,0.0000638167,0.00003502538,0.0002092094,0.0004906868,0.00005502556,0.0007768752,0.9746361,0.004089281],"study_design_scores_gemma":[0.0002598443,0.00001948686,0.2375938,0.001233941,0.0001005444,0.0000719129,0.00143685,0.0008057677,0.0003178467,0.0006905788,0.7573818,0.00008759728],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006749192,0.00008786854,0.00002656412,0.00009614296,0.0000139853,0.00001360436,0.9983216,0.00003528917,0.0007300274],"genre_scores_gemma":[0.003724809,0.0002142114,0.0002068493,0.00006364899,0.000009054298,0.0001185692,0.9923452,0.00003117,0.003286501],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02725112,"threshold_uncertainty_score":0.1111759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081115508758647,"score_gpt":0.2869672769294465,"score_spread":0.27615612184186,"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."}}