{"id":"W6920290380","doi":"10.6068/dp14ba8fac62324","title":"Trend 2000 - 2006. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household, Family and Personal Income | Country: Canada | Table: Seniors' characteristics, by family type, age of oldest individual and source of income | Variable: 75 years and over, Lone-parent families and persons not in census families, Number in family type, Registered Retirement Savings Plan (RRSP) | Units: , 2000-2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-119.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Personal income; Demographic statistics; Socioeconomic status; Economic statistics; Official statistics; Population; Family income; Transfer payment; 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":[0.002236361,0.00252542,0.003109583,0.007799422,0.002978491,0.004742055,0.005473312,0.00137181,0.08649236],"category_scores_gemma":[0.01807813,0.001954508,0.002285399,0.04023372,0.0005913768,0.002475185,0.002418251,0.003361745,0.05221965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05367066,"about_ca_system_score_gemma":0.1231222,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9940503,"about_ca_topic_score_gemma":0.9919077,"domain_scores_codex":[0.9959561,0.0002666313,0.0005126818,0.0005170183,0.001853357,0.0008942467],"domain_scores_gemma":[0.9633052,0.001264212,0.001200564,0.001068562,0.03152564,0.001635834],"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":[0.00003112352,0.000007485311,0.001274836,0.0002791359,0.000023514,0.000006439861,0.000022706,0.0001019163,0.000008014376,0.0003143465,0.996079,0.001851405],"study_design_scores_gemma":[0.0002184901,0.00001663754,0.03450529,0.001091087,0.0000834902,0.00003156107,0.0004994748,0.0005159283,0.0001824728,0.0007112074,0.962044,0.0001004852],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005783387,0.00004739917,0.00002031595,0.0001029831,0.00002380231,0.00001468828,0.9989539,0.0000531088,0.0007258435],"genre_scores_gemma":[0.0007498931,0.000259056,0.0003365852,0.0001325824,0.00001540954,0.000126734,0.9945169,0.00008917715,0.003773559],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08649236,"threshold_uncertainty_score":0.3894097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04100892721855163,"score_gpt":0.2570349969673743,"score_spread":0.2160260697488226,"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."}}