{"id":"W6939142200","doi":"10.6068/dp14ba8bcd2a223","title":"Trend 2007 - 2011. Statistics Canada. CANSIM: Population and Demography - Population Estimates and Projections | Country: Canada | Table: Neighbourhood income and demographics, taxfilers and dependents with income, by sex, age group, income taxes paid and after-tax income | Variable: 65 years and over, Number of taxfilers and dependents, Income taxes paid, Both sexes | Units: #, 2007-2011. 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; Residence; Socioeconomic status; Population statistics; Demographic statistics; Neighbourhood (mathematics); Economic statistics; Social 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":[0.002449438,0.002289679,0.002525009,0.007000507,0.003112479,0.004213453,0.004821524,0.001337261,0.09385645],"category_scores_gemma":[0.01734133,0.001723209,0.002208558,0.03171047,0.000606567,0.002150602,0.002543516,0.003113071,0.04834164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05583384,"about_ca_system_score_gemma":0.1453068,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958363,"about_ca_topic_score_gemma":0.9941446,"domain_scores_codex":[0.9964766,0.0002930972,0.0004014391,0.0003906676,0.001643522,0.0007946614],"domain_scores_gemma":[0.9696745,0.0009083933,0.0006719652,0.0008027088,0.02653556,0.001406961],"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":[0.0000270773,0.000007008267,0.0009461567,0.0002731388,0.00002491989,0.00000812829,0.00003155684,0.0001662025,0.00001123817,0.0004651017,0.9948972,0.003142255],"study_design_scores_gemma":[0.0001934298,0.0000160272,0.02504491,0.001065997,0.00009221285,0.00003868013,0.0005651335,0.0009490797,0.0002024496,0.0009278192,0.9707934,0.0001107932],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000975302,0.00009569499,0.00008122875,0.0002179303,0.00006079049,0.00003759902,0.9973869,0.0001367794,0.0018856],"genre_scores_gemma":[0.001670514,0.0005789581,0.001235043,0.0003006031,0.00002947555,0.0002752187,0.9884707,0.0002394012,0.007200077],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09385645,"threshold_uncertainty_score":0.4051048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008214358632837,"score_gpt":0.2331626578976173,"score_spread":0.2230805143112889,"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."}}