{"id":"W6957973973","doi":"10.6068/dp14ba84809dd91","title":"Trend 2010 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household Spending and Savings | Country: Canada | Table: Survey of household spending (SHS), household spending | Variable: Average expenditure per household, Total expenditure | Units: $CAD, 2010-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-120.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"X-ray Diffraction in Crystallography","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Consumer Expenditure Survey; Summary statistics; Official statistics; Census; Population; Descriptive statistics; Household income; Socioeconomic status; National accounts","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","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.003592886,0.00236551,0.00322312,0.0008630291,0.0009170879,0.001235247,0.004030128,0.0015231,0.01219563],"category_scores_gemma":[0.0003180141,0.002368988,0.000002382699,0.000595408,0.0008829895,0.001860318,0.003133591,0.002938596,0.00005367288],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007983546,"about_ca_system_score_gemma":0.006827753,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9987403,"about_ca_topic_score_gemma":0.9903017,"domain_scores_codex":[0.9861327,0.001421395,0.002750862,0.003786835,0.003327345,0.002580846],"domain_scores_gemma":[0.9864486,0.002785491,0.003348807,0.005381384,0.0001103326,0.001925415],"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":[0.0002605072,0.0001582107,0.003110313,0.001141834,0.0003628969,0.001343073,0.00001388403,0.0001705069,0.000874062,0.0002753191,0.9922707,0.00001870253],"study_design_scores_gemma":[0.001876912,0.0001441997,0.001645527,0.0002917869,0.0006305281,0.001461771,0.0005749517,0.0003477227,0.000003512564,9.386788e-7,0.9905071,0.002515096],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004649547,0.003665774,0.00004101791,0.00000442923,0.006798119,0.001517561,0.9862625,0.0003658354,0.0008797969],"genre_scores_gemma":[0.006077026,0.00373165,0.0009102514,0.0001477482,0.0007868629,0.00003024074,0.9848121,0.001032936,0.00247123],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01214196,"threshold_uncertainty_score":0.9998016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04348049456464276,"score_gpt":0.2533303743558511,"score_spread":0.2098498797912083,"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."}}