{"id":"W6963640703","doi":"10.25318/9810061801-eng","title":"Mother tongue by immigrant status and period of immigration and number of languages known: 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":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Metropolitan area; Immigration; Urban agglomeration; Population; Period (music)","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":[0.000836033,0.001580324,0.001571647,0.004611402,0.001786664,0.002296981,0.003357697,0.001177989,0.04181743],"category_scores_gemma":[0.006798955,0.001033939,0.001305484,0.01704459,0.0004389524,0.001047298,0.001332873,0.001908799,0.01555987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01629177,"about_ca_system_score_gemma":0.03531565,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9760512,"about_ca_topic_score_gemma":0.9811536,"domain_scores_codex":[0.9988423,0.00005614154,0.0001260082,0.0001855273,0.0003779214,0.0004121963],"domain_scores_gemma":[0.9939904,0.0003547372,0.0004276838,0.0002589154,0.004290092,0.0006783323],"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":[0.00005032822,0.00001361499,0.004398705,0.0003374684,0.00003538015,0.00001855435,0.00004282223,0.0001453445,0.00001771999,0.0003707501,0.9928934,0.001675839],"study_design_scores_gemma":[0.0004444989,0.000023069,0.1692536,0.001546357,0.0001343329,0.0001217538,0.0007109691,0.0007597591,0.0003564682,0.0007938445,0.8257611,0.00009438187],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002286474,0.00005262654,0.00001595692,0.00004209581,0.00001070041,0.00001183819,0.9991585,0.0000220132,0.0004576431],"genre_scores_gemma":[0.002266842,0.0001867625,0.0001930752,0.00008750745,0.000008680861,0.000134601,0.9944476,0.0000315761,0.0026434],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04181743,"threshold_uncertainty_score":0.1398932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003763959060322131,"score_gpt":0.251208594484175,"score_spread":0.2474446354238529,"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."}}