{"id":"W6901572518","doi":"10.6068/dp14ba89421d311","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: All age groups, Persons with income of $100,000 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; Residence; Socioeconomic status; 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":[0.002338905,0.00229976,0.002456224,0.006500822,0.003166108,0.004439015,0.005140333,0.001388877,0.1051985],"category_scores_gemma":[0.0176688,0.001685285,0.00218924,0.03047061,0.0005799101,0.002349555,0.0025737,0.003234604,0.05983505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04865703,"about_ca_system_score_gemma":0.1205653,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947467,"about_ca_topic_score_gemma":0.9930225,"domain_scores_codex":[0.9967551,0.0002822481,0.0003789706,0.0003949303,0.00147302,0.0007157726],"domain_scores_gemma":[0.9727984,0.0008251403,0.0005875016,0.0008205837,0.02370454,0.001263884],"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":[0.00002369067,0.000005855448,0.0007931651,0.0002466566,0.00002143047,0.000007511807,0.00002821306,0.0001481133,0.000009226991,0.00041924,0.9955369,0.002759975],"study_design_scores_gemma":[0.0001810226,0.00001250659,0.01883953,0.0009604152,0.00007884072,0.0000350691,0.0004808515,0.0008030997,0.0001729415,0.0009906442,0.977344,0.0001010984],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006794569,0.00007714381,0.00006946132,0.0001836211,0.00005141681,0.00003152,0.9977024,0.000123602,0.001692833],"genre_scores_gemma":[0.001242913,0.0004635959,0.001042093,0.0002543536,0.00002528279,0.0002463634,0.9905424,0.0002176917,0.005965345],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1051985,"threshold_uncertainty_score":0.3530331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287482732655173,"score_gpt":0.2297546828544174,"score_spread":0.2168798555278656,"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."}}