{"id":"W6901655556","doi":"10.6068/dp14ba8d08ed97","title":"Trend 1997 - 2009. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household Spending and Savings | Country: Canada | Table: Survey of household spending (SHS), household spending on personal insurance payments and pension contributions | Variable: Total personal insurance payments and pension contributions, Estimated number of households reporting | Units: , 1997-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-120.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Plant-Microbe Interactions and Immunity","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Personal income; Descriptive statistics; Census; Household income; Payment; Socioeconomic status; Official statistics; Economic statistics; Pension; Summary 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":[0.002292627,0.002435465,0.002649749,0.007334534,0.003365218,0.004475585,0.005144499,0.0013611,0.08515044],"category_scores_gemma":[0.01622489,0.001754089,0.002136563,0.035851,0.0005752293,0.002345085,0.002398743,0.003192679,0.05006929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05060887,"about_ca_system_score_gemma":0.1216088,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948067,"about_ca_topic_score_gemma":0.993176,"domain_scores_codex":[0.9959372,0.0002706006,0.0004326574,0.0004834543,0.001895662,0.0009803989],"domain_scores_gemma":[0.9721645,0.0009225973,0.000831089,0.0008253508,0.02385496,0.001401531],"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":[0.000026437,0.000006776038,0.00110096,0.0002335273,0.00002056404,0.000006598047,0.0000224666,0.00009000216,0.000008624585,0.000365866,0.9963492,0.001769068],"study_design_scores_gemma":[0.0001803601,0.00001466421,0.03263381,0.0009474367,0.00007612922,0.00002902708,0.0005212522,0.0004810249,0.0001893726,0.0006995924,0.964133,0.00009442647],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000571697,0.00004443896,0.00002255317,0.0001159185,0.00002320907,0.00001594443,0.99882,0.00004889069,0.0008519479],"genre_scores_gemma":[0.0008198154,0.0002613839,0.0003898456,0.0001484009,0.00001569617,0.000137527,0.9941106,0.00009327206,0.004023448],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08515044,"threshold_uncertainty_score":0.3671948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04982624310432865,"score_gpt":0.2741354981484522,"score_spread":0.2243092550441235,"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."}}