{"id":"W6920109617","doi":"10.6068/dp14ba903962f72","title":"Trend 2006 - 2012. Statistics Canada. CANSIM: Crime and Justice - Civil Courts and Family Law | Country: Canada | Table: Survey of Maintenance Enforcement Programs (SMEP), enrolled cases, by activity status, compliance with regular and total payments, arrears status and assignment status at March 31 | Variable: Total active cases, Total arrears status at beginning of March of fiscal year, Partial compliance with payment in March of the fiscal yearage of cases, Non-assigned payment, Regular payment due | 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":"Arrears; Law enforcement; Payment; Enforcement; Economic statistics; Economic Justice; Alimony; Census","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":[0.002121763,0.002332628,0.00281155,0.00904603,0.003125226,0.004496469,0.005280272,0.001466986,0.08218446],"category_scores_gemma":[0.02046432,0.00189009,0.001996504,0.03826364,0.0006179131,0.002289985,0.002440914,0.003120217,0.03982844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0534369,"about_ca_system_score_gemma":0.1300502,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944721,"about_ca_topic_score_gemma":0.9933462,"domain_scores_codex":[0.9960064,0.0002770367,0.0005211626,0.0005401429,0.001705677,0.0009495346],"domain_scores_gemma":[0.962924,0.001470103,0.001478697,0.001060918,0.03086843,0.002197875],"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":[0.00002605005,0.000008620556,0.001451685,0.0002484262,0.00002209986,0.000006253056,0.00002503198,0.00009432028,0.000007094025,0.0002981143,0.996429,0.001383306],"study_design_scores_gemma":[0.0002876469,0.00002320404,0.05268537,0.001476906,0.0001152718,0.00004023163,0.0008608361,0.0007220933,0.0002130132,0.0008340304,0.9426262,0.0001151548],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007038987,0.00004180265,0.00001842474,0.0001052876,0.00002208042,0.00001630114,0.9990728,0.00004463665,0.0006081505],"genre_scores_gemma":[0.0009750637,0.0002506453,0.0002831003,0.0001461172,0.00001824507,0.0001364803,0.99498,0.00007316524,0.003137045],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08218446,"threshold_uncertainty_score":0.3877137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03120898671344855,"score_gpt":0.2588058550505263,"score_spread":0.2275968683370777,"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."}}