{"id":"W6957952021","doi":"10.6068/dp14ba891bd7753","title":"Trend 1997 - 2009. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household Spending and Savings | Country: Canada | Table: Survey of household spending (SHS), dwelling characteristics at the time of interview | Variable: Dwellings needing minor repairs, Estimated number of households reporting | Units: % of households responding x 1,000, 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; Census; Official statistics; Summary statistics; Socioeconomic status; Population; Household income; Goods and services; National accounts; Population 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":[0.002410221,0.002327065,0.002554724,0.007009923,0.003064739,0.004174603,0.005173394,0.001291957,0.08605411],"category_scores_gemma":[0.01624227,0.001774774,0.002197988,0.03548202,0.0005476207,0.002284894,0.002371031,0.003158782,0.04667225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04974675,"about_ca_system_score_gemma":0.1197968,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945749,"about_ca_topic_score_gemma":0.9927417,"domain_scores_codex":[0.9958577,0.000284914,0.0004587896,0.0004809656,0.001951957,0.0009656983],"domain_scores_gemma":[0.9717574,0.0009636493,0.0008473259,0.0007888608,0.02427605,0.00136676],"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":[0.00002892117,0.000007609789,0.001224919,0.0002779827,0.00002260258,0.000006691444,0.00002432493,0.00009111527,0.00000853118,0.000359885,0.9960108,0.001936514],"study_design_scores_gemma":[0.0001950433,0.00001730794,0.03929809,0.001061549,0.000086494,0.00003201991,0.0005907428,0.000487373,0.0001872803,0.0006587271,0.957292,0.00009342015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006177696,0.00004913119,0.00002302491,0.0001192442,0.00002537932,0.00001798568,0.9987699,0.00004671497,0.0008868281],"genre_scores_gemma":[0.0009132015,0.0003055457,0.000417319,0.0001654414,0.00001700035,0.0001592045,0.9931006,0.00009573132,0.004825844],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08605411,"threshold_uncertainty_score":0.3609396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06747896930816807,"score_gpt":0.2847509714027745,"score_spread":0.2172720020946064,"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."}}