{"id":"W6939175919","doi":"10.6068/dp14ba90210bb6","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 active cases, Non-interjurisdictional support order, Total number of cases, Full compliance with payment in all 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; Census; Child support; 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":[0.002185625,0.002380599,0.002925964,0.009885754,0.003364233,0.004716652,0.005475446,0.001480276,0.0846362],"category_scores_gemma":[0.02033343,0.002067767,0.00204736,0.04097037,0.0006264416,0.002432319,0.002423364,0.003208305,0.03771663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06258674,"about_ca_system_score_gemma":0.1534351,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9956133,"about_ca_topic_score_gemma":0.9943193,"domain_scores_codex":[0.9953921,0.0002836111,0.0005923512,0.0005642084,0.002114045,0.001053714],"domain_scores_gemma":[0.9571921,0.001546393,0.001613037,0.001005749,0.03629774,0.002344904],"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":[0.00002804818,0.0000102376,0.001708446,0.0002770569,0.00002401643,0.000007022458,0.00002821895,0.0001052294,0.000007683699,0.0003417981,0.995799,0.001663203],"study_design_scores_gemma":[0.0002768577,0.00002616824,0.06283237,0.001584088,0.0001261172,0.0000444771,0.0009673808,0.0007982598,0.0002376524,0.0007964648,0.9321881,0.0001221052],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000900351,0.00005307731,0.00002054002,0.0001341548,0.00002743918,0.0000202788,0.998752,0.00005100833,0.0008514663],"genre_scores_gemma":[0.001275174,0.0003546225,0.0003479485,0.0001971282,0.00002289942,0.0001588717,0.9927763,0.00009319386,0.004773901],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0846362,"threshold_uncertainty_score":0.4541007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03044921818494616,"score_gpt":0.2735462715869878,"score_spread":0.2430970534020416,"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."}}