{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001933426,0.001044842,0.00201039,0.0001923649,0.0001551289,0.0001329991,0.001116803,0.0004878716,0.0003550776],"category_scores_gemma":[0.0005346768,0.0008158096,0.000001394749,0.0005737115,0.0006065043,0.0005070628,0.0007242905,0.0007487485,0.000001614437],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005847373,"about_ca_system_score_gemma":0.01186243,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9998474,"about_ca_topic_score_gemma":0.9997514,"domain_scores_codex":[0.9934117,0.0008600822,0.001366516,0.001333425,0.001487071,0.001541206],"domain_scores_gemma":[0.9906279,0.00482387,0.001726925,0.002010681,0.0003316458,0.0004789893],"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":[0.007870161,0.0006108666,0.0001703792,0.001077774,0.0007298635,0.0002560151,0.00004868779,0.00005671539,0.00001050794,0.0006162089,0.9874081,0.001144739],"study_design_scores_gemma":[0.00458032,0.0008679755,0.0009889406,0.0002330367,0.0010451,0.0001289909,0.001174118,0.00427024,2.400018e-7,3.469206e-7,0.9858597,0.0008509899],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006363267,0.007052733,0.000002593468,0.000003863329,0.0004834707,0.005609187,0.9860582,0.00002542576,0.000128244],"genre_scores_gemma":[0.01165396,0.002812687,0.00008050563,0.0001046439,0.0001294789,0.0003013517,0.9840764,0.0003614851,0.0004794798],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01127769,"threshold_uncertainty_score":0.9994293,"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."}}