{"id":"W6957948848","doi":"10.6068/dp14ba88d23ae57","title":"Trend 2000 - 2011. Statistics Canada. CANSIM: Population and Demography - Population Estimates and Projections | Country: Canada | Table: Neighbourhood income and demographics, taxfilers and dependents with income by total income, sex and age group | Variable: 0 to 24 years, Persons with income of $50,000 and over, Both sexes | Units: #, 2000-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-163.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Census; Socioeconomic status; Residence; Population statistics; Social statistics; Neighbourhood (mathematics); Economic statistics; Demographic statistics","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":[0.002361385,0.002352289,0.002428308,0.006584243,0.003161744,0.004348611,0.005093766,0.001354964,0.1032326],"category_scores_gemma":[0.01793457,0.001699694,0.002145613,0.03058679,0.0005827898,0.0023078,0.002541845,0.003205378,0.05674005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04826065,"about_ca_system_score_gemma":0.1195738,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994859,"about_ca_topic_score_gemma":0.9931633,"domain_scores_codex":[0.9968106,0.0002791811,0.000373713,0.0003876233,0.00144587,0.0007029096],"domain_scores_gemma":[0.9725102,0.0008534798,0.0005958266,0.0008112025,0.02395102,0.00127838],"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":[0.00002310574,0.000005771797,0.0007705567,0.0002338293,0.00002056872,0.000007251485,0.0000278042,0.0001457674,0.000008810731,0.0004077283,0.99565,0.002698901],"study_design_scores_gemma":[0.0001868373,0.0000130831,0.0189992,0.0009465739,0.0000765876,0.00003562806,0.0004788113,0.0008653508,0.0001703309,0.001006783,0.9771195,0.0001012335],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006950325,0.00007465939,0.00006895264,0.000181442,0.00004941753,0.00003098233,0.9977897,0.000125476,0.001609863],"genre_scores_gemma":[0.001206487,0.0004381547,0.000987038,0.0002390975,0.00002425307,0.0002380162,0.9911703,0.0002091833,0.005487406],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1032326,"threshold_uncertainty_score":0.3501571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147468910955223,"score_gpt":0.2264110730860755,"score_spread":0.2149363839765233,"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."}}