{"id":"W6920437340","doi":"10.6068/dp14ba8235b3298","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 transportation | Variable: Average expenditure, Total transportation | 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Summary statistics; Census; Household income; Socioeconomic status; Goods and services; National accounts; Population; Consumer Expenditure Survey","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002204548,0.002320577,0.002557756,0.007256709,0.003240525,0.004464631,0.004995764,0.001330139,0.08379918],"category_scores_gemma":[0.01575398,0.00172078,0.002156274,0.03487282,0.0005542392,0.002430986,0.002332958,0.00332826,0.04554347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05380728,"about_ca_system_score_gemma":0.1200369,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947684,"about_ca_topic_score_gemma":0.9930984,"domain_scores_codex":[0.9960898,0.0002583,0.0004091581,0.0004518986,0.001869727,0.0009210887],"domain_scores_gemma":[0.9725022,0.0008497458,0.0007311399,0.0007567799,0.023846,0.001314019],"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":[0.00002706792,0.000007061972,0.001175771,0.0002539884,0.00002201093,0.000007062497,0.00002412942,0.00009744104,0.000009086762,0.0004560683,0.9959364,0.001983921],"study_design_scores_gemma":[0.0001668138,0.000015094,0.03376947,0.0009674427,0.00008015762,0.0000320708,0.0005416337,0.0005047015,0.0001854213,0.0007655817,0.9628765,0.00009506353],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006359105,0.00005674561,0.00002600375,0.0001300592,0.00002800659,0.00001839483,0.9986368,0.00005071551,0.0009897262],"genre_scores_gemma":[0.001004153,0.0003308644,0.0004475652,0.0001619876,0.00001771144,0.0001499846,0.9932269,0.0001046532,0.004556131],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9162008,"threshold_uncertainty_score":0.390401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04501576261573838,"score_gpt":0.2544493020275991,"score_spread":0.2094335394118607,"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."}}