{"id":"W4246740786","doi":"10.4095/301432","title":"Mother Tongue, 2006 - Other Languages (by census division)","year":2010,"lang":"en","type":"report","venue":"","topic":"Multilingual Education and Policy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Division (mathematics); Census; Tongue; Genealogy; Linguistics; Geography; Computer science; History; Arithmetic; Mathematics; Sociology; Demography; Philosophy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003715246,0.0007996964,0.0002555706,0.003358634,0.001019355,0.0009738327,0.0009339294,0.0002893749,0.01538823],"category_scores_gemma":[0.001704191,0.000343059,0.0003169064,0.006102616,0.0001275732,0.0007539586,0.0007850283,0.000663703,0.007477816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003532204,"about_ca_system_score_gemma":0.006030235,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6392429,"about_ca_topic_score_gemma":0.8107399,"domain_scores_codex":[0.9993149,0.00002660876,0.00007221653,0.00005351191,0.0003657608,0.0001670512],"domain_scores_gemma":[0.998557,0.00004210266,0.0001969925,0.00004136706,0.00100009,0.000162512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000208678,0.0002437744,0.2205702,0.0007231798,0.00005595993,0.0003198999,0.001477165,0.0003274952,0.0007404417,0.001052402,0.7276715,0.04660919],"study_design_scores_gemma":[0.0000278051,0.00003803771,0.8206945,0.000176745,0.0000175394,0.0001442318,0.001249745,0.000164567,0.0004299511,0.00006472209,0.1769787,0.00001348404],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.05491127,0.0008077135,0.0001731697,0.0004964105,0.0001772035,0.0004491007,0.8933633,0.0001343896,0.04948739],"genre_scores_gemma":[0.08056228,0.004431663,0.001469636,0.0004247056,0.00009221995,0.001008218,0.8021354,0.00007852272,0.1097974],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3607571,"threshold_uncertainty_score":0.7257633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07983073356314944,"score_gpt":0.5186816819526852,"score_spread":0.4388509483895357,"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."}}