{"id":"W6889059265","doi":"10.25318/9810018101-eng","title":"Mother tongue by single and multiple mother tongue responses: Canada, provinces and territories, census metropolitan areas and census agglomerations with parts","year":2022,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Urban agglomeration; Population; Demographic analysis","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"],"consensus_categories":[],"category_scores_codex":[0.0002601509,0.000699569,0.0005902599,0.000236331,0.0007877981,0.0003052821,0.0002161746,0.0001574824,0.000357742],"category_scores_gemma":[0.001257368,0.0007011438,0.00001223228,0.0003619987,0.0003852787,0.0001514197,0.0001230092,0.0004102681,2.042175e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003972415,"about_ca_system_score_gemma":0.002230555,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948812,"about_ca_topic_score_gemma":0.999804,"domain_scores_codex":[0.9962271,0.0003493526,0.0005662297,0.0009316418,0.00129189,0.0006337619],"domain_scores_gemma":[0.9968698,0.001206175,0.0005778112,0.000531105,0.0003361262,0.0004789817],"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":[0.0001875992,0.00008679117,0.000911566,0.0002330727,0.0001491253,0.0002267898,0.0001075541,0.000006438142,0.00009977131,0.0002260842,0.9972282,0.0005369962],"study_design_scores_gemma":[0.0005950474,0.0002428917,0.00678958,0.0001208514,0.0003229259,0.00007800263,0.003279638,0.0001420757,0.00009851921,0.00003580602,0.9873674,0.0009272966],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003817054,0.001326215,0.00002894174,0.0002215089,0.0003405731,0.0009103547,0.9932861,0.00003206809,0.00003720188],"genre_scores_gemma":[0.01626601,0.00008690567,0.0006030577,0.00009017498,0.00008508625,0.0001398062,0.9814025,0.000171369,0.001155093],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01244895,"threshold_uncertainty_score":0.9998512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006983341460365503,"score_gpt":0.2363596652530099,"score_spread":0.2293763237926444,"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."}}