{"id":"W6901440921","doi":"10.6068/dp14ba90203340","title":"Trend 2006 - 2012. Statistics Canada. CANSIM: Crime and Justice - Civil Courts and Family Law | Country: Canada | Table: Survey of Maintenance Enforcement Programs (SMEP), cases enrolled, by activity status, type of beneficiary, interjurisdictional support order status and regularity of compliance | Variable: Total all cases, Non-interjurisdictional support order, Total number of cases, Full compliance with payment in 3 to 5 months of the fiscal year, Spouse and children as beneficiaries | Units: #, 2006-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-038.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Law enforcement; Enforcement; Economic Justice; Alimony; Economic statistics; Payment; Child support; Census; Spouse","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":[0.002046934,0.0022868,0.002772827,0.009210802,0.003144544,0.004571631,0.005394288,0.001468992,0.08021783],"category_scores_gemma":[0.01978404,0.001862298,0.002071975,0.03875007,0.0006014861,0.002233159,0.002355766,0.003096188,0.03719541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05636318,"about_ca_system_score_gemma":0.1324942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946476,"about_ca_topic_score_gemma":0.9935859,"domain_scores_codex":[0.9959069,0.0002724072,0.0005356263,0.0005276494,0.00180651,0.0009508127],"domain_scores_gemma":[0.9626632,0.001446654,0.001458126,0.00100717,0.0313206,0.002104274],"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":[0.00002669259,0.000008934267,0.001533335,0.00026218,0.00002325517,0.000006893195,0.00002572798,0.00009905496,0.000007312264,0.0003370667,0.9961818,0.001487706],"study_design_scores_gemma":[0.0002675761,0.00002151674,0.05159964,0.001519007,0.0001206706,0.00004294659,0.0008465896,0.0007190373,0.0002134727,0.0008158474,0.9437206,0.000113133],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007379032,0.00004837322,0.0000183959,0.0001120721,0.00002264577,0.00001649996,0.9989699,0.00004378855,0.0006944916],"genre_scores_gemma":[0.001012939,0.0002884415,0.0002971453,0.0001541844,0.00001845219,0.0001326714,0.9946529,0.00007346548,0.003369931],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08021783,"threshold_uncertainty_score":0.4089454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02865970970164765,"score_gpt":0.2718464358941686,"score_spread":0.243186726192521,"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."}}