{"id":"W6907739497","doi":"10.25318/9810036101-eng","title":"Non-permanent resident type by place of birth: Canada, provinces and territories, census metropolitan areas and census agglomerations with parts","year":2023,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Urban agglomeration; Population; American Community Survey","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":[0.001014466,0.001814867,0.00206005,0.005380481,0.001972514,0.00256701,0.003992434,0.001269089,0.0469712],"category_scores_gemma":[0.008015451,0.001211237,0.001605254,0.02269965,0.0004994817,0.001278641,0.00146797,0.002261831,0.01819534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01994871,"about_ca_system_score_gemma":0.05013226,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9828854,"about_ca_topic_score_gemma":0.9848431,"domain_scores_codex":[0.9983904,0.00007657713,0.0001988424,0.0002537839,0.0005426029,0.0005377758],"domain_scores_gemma":[0.9925048,0.0003940476,0.0004847506,0.000325955,0.005561429,0.0007289906],"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":[0.00004721475,0.00001235083,0.003326833,0.0004319001,0.00004041948,0.0000169807,0.00003742388,0.0001719912,0.0000170752,0.0004443588,0.9938599,0.001593537],"study_design_scores_gemma":[0.00048498,0.00002095556,0.1201777,0.001431425,0.000132972,0.00009927829,0.0005554514,0.0007155751,0.0003119348,0.0009360889,0.8750475,0.00008621204],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001333971,0.00004685296,0.00001831908,0.00003497501,0.00001124418,0.00001132965,0.9993317,0.00002311848,0.0003890149],"genre_scores_gemma":[0.001734332,0.0001750679,0.0002337874,0.00007895167,0.000008610917,0.0001334297,0.9952997,0.00003713573,0.002299036],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0469712,"threshold_uncertainty_score":0.1571344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006239993486754537,"score_gpt":0.248312396157066,"score_spread":0.2420724026703115,"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."}}