{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001946911,0.0008726534,0.00159438,0.0001043534,0.0008569427,0.0003653492,0.0006331083,0.0004675686,0.0003334827],"category_scores_gemma":[0.0008484889,0.0005963507,0.000001491077,0.0005672966,0.0003982811,0.0005978578,0.0009179356,0.001152729,0.00000185486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003394606,"about_ca_system_score_gemma":0.001118894,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944209,"about_ca_topic_score_gemma":0.952022,"domain_scores_codex":[0.9941066,0.0006665126,0.001821784,0.001356724,0.001067682,0.0009807124],"domain_scores_gemma":[0.9939719,0.001966558,0.002713766,0.0005726986,0.0001311377,0.0006439597],"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":[0.0002620851,0.0001431961,0.06435598,0.0002662839,0.0001913454,0.0002925257,0.000005528676,0.000007638844,0.001292655,0.00006527546,0.9329558,0.0001616898],"study_design_scores_gemma":[0.001448929,0.000221224,0.1039486,0.0009319495,0.0002567722,0.001939823,0.0003423614,0.001273449,0.000005249539,4.477487e-7,0.8885747,0.001056506],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.10545,0.001594627,0.000001527386,0.000004872385,0.0004438696,0.0006184574,0.8917317,0.00006351331,0.00009137069],"genre_scores_gemma":[0.3209604,0.002265532,0.00005912765,0.0000409407,0.00006845364,0.000004438921,0.6764337,0.00003792622,0.0001294691],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2155104,"threshold_uncertainty_score":0.9996488,"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."}}