{"id":"W6950753133","doi":"10.5683/sp2/7wr7fg","title":"2016 Census of Canada - Selected Characteristics for Housing - Vancouver, Toronto, Montreal CMAs at the Census Tract (CT) Level [custom tabulation] 001","year":2019,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Census tract; Bedroom; Subsidy; Table (database); Order (exchange); Household income","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":[0.0005805459,0.001104797,0.001531521,0.00013329,0.0005288473,0.00008943376,0.001090601,0.0004790009,0.0002392927],"category_scores_gemma":[0.000915891,0.0008475371,0.0002734825,0.0003311801,0.0001805558,0.0002268289,0.0002343227,0.0004559713,0.00001263954],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005589544,"about_ca_system_score_gemma":0.003650768,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9966133,"about_ca_topic_score_gemma":0.9996685,"domain_scores_codex":[0.9944628,0.0002814175,0.001456697,0.000983111,0.001430584,0.001385381],"domain_scores_gemma":[0.9925067,0.001005611,0.002486655,0.002252279,0.001412026,0.0003367281],"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":[0.0005336331,0.0002411741,0.00004906703,0.0003031006,0.000400524,0.00006459421,0.00003586229,0.0001127505,0.00008260104,0.000003074852,0.996973,0.001200586],"study_design_scores_gemma":[0.001940825,0.0000867129,0.01666961,0.0001841196,0.0009361443,0.00003565371,0.0000595091,0.0004437019,0.00006980147,0.000004989586,0.9785954,0.0009735315],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005559545,0.0005125538,0.000006501386,0.00004639491,0.001814059,0.002180529,0.9944794,0.00008569604,0.0003189506],"genre_scores_gemma":[0.0007090245,0.0002222073,0.0001034406,0.0001059433,0.0008620789,0.0001216572,0.9959781,0.0003215953,0.001575988],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01837763,"threshold_uncertainty_score":0.9993975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02749317480410477,"score_gpt":0.2560648537570924,"score_spread":0.2285716789529876,"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."}}