{"id":"W6957931914","doi":"10.6068/dp14ba8dcaef391","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 for the entire fiscal year, by activity status, type of beneficiary, change in arrears, length of enrolment | Variable: Total active cases, Total change in arrears status, Enrolled for 5 years or less, Spouse as the only beneficiary | 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; Alimony; Law enforcement; Economic statistics; Enforcement; Economic Justice; Official statistics; Social statistics; Descriptive 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":[0.002446065,0.002547836,0.002991543,0.009604648,0.003360518,0.004792803,0.005471602,0.001516786,0.08863607],"category_scores_gemma":[0.02149722,0.002071606,0.002200342,0.04134063,0.0006415041,0.002526929,0.002451502,0.003249887,0.0443537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06095962,"about_ca_system_score_gemma":0.1527053,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955695,"about_ca_topic_score_gemma":0.9941818,"domain_scores_codex":[0.9952281,0.000321266,0.0005981667,0.0005832242,0.002210667,0.001058617],"domain_scores_gemma":[0.9562202,0.001522662,0.001516956,0.001084744,0.03741978,0.00223563],"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":[0.00002710734,0.000008485808,0.001364415,0.0002654614,0.00002335876,0.000006267996,0.00002435412,0.00009547199,0.000007626255,0.0003041371,0.9963057,0.001567683],"study_design_scores_gemma":[0.0002579587,0.00002247705,0.04853392,0.001374649,0.0001155211,0.00003776161,0.0007529029,0.0006549829,0.0002091266,0.0007353027,0.947189,0.0001163181],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007047694,0.00005417845,0.00002093787,0.0001385423,0.00003032699,0.00001909976,0.9988035,0.00005389619,0.0008089705],"genre_scores_gemma":[0.001043676,0.0003338675,0.0003616639,0.0001941625,0.00002294489,0.0001531767,0.993335,0.00009977924,0.004455821],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08863607,"threshold_uncertainty_score":0.4422951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06162825142498465,"score_gpt":0.2910673859680921,"score_spread":0.2294391345431075,"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."}}