{"id":"W6920625946","doi":"10.6068/dp14ba901301a13","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, Interjurisdictional support order-in, Total number of cases, Full compliance with payment in 9 to 11 months of the fiscal year, 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":"Law enforcement; Enforcement; Alimony; Economic Justice; Economic statistics; Beneficiary; Arrears; Child support; Payment","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":[0.002011102,0.002301893,0.002783125,0.009233707,0.003127624,0.004572538,0.005388959,0.001466958,0.08059093],"category_scores_gemma":[0.01961726,0.001868931,0.002056265,0.03900017,0.000598689,0.002246144,0.002355041,0.003088903,0.03706932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05639984,"about_ca_system_score_gemma":0.1316402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946414,"about_ca_topic_score_gemma":0.9935861,"domain_scores_codex":[0.9959593,0.0002663917,0.0005305193,0.0005239315,0.001779355,0.0009404876],"domain_scores_gemma":[0.9626257,0.001436321,0.001458144,0.0009963996,0.0313792,0.002104173],"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":[0.0000269398,0.000009009343,0.001538258,0.0002642467,0.00002322465,0.000006912645,0.00002566452,0.0000999385,0.000007324767,0.0003347493,0.9961889,0.001474843],"study_design_scores_gemma":[0.0002725932,0.00002193129,0.0532753,0.001519417,0.0001226877,0.00004359808,0.0008648381,0.0007322436,0.0002180528,0.0008180968,0.9419953,0.0001160111],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007356628,0.00004730593,0.00001791965,0.0001094311,0.00002218415,0.00001622563,0.9989923,0.00004301843,0.0006780321],"genre_scores_gemma":[0.001012864,0.0002832382,0.0002897975,0.0001504928,0.00001822536,0.0001306216,0.9947445,0.00007231158,0.003297896],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08059093,"threshold_uncertainty_score":0.4092114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03558038480942545,"score_gpt":0.278552122285505,"score_spread":0.2429717374760795,"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."}}