{"id":"W6976816007","doi":"10.6068/dp14ba8fbaf4923","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, No arrears at beginning of year and change in arrears unknown, Enrolled for more than 10 years, 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":"Arrears; Alimony; Law enforcement; Enforcement; Economic statistics; Economic Justice; Payment; Official statistics; Child support","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":[0.00246935,0.002499801,0.00302993,0.00931865,0.003446939,0.004791423,0.005587211,0.001521408,0.08219565],"category_scores_gemma":[0.02090198,0.002081364,0.002220559,0.03955214,0.0006385673,0.0024484,0.002479617,0.003289703,0.04015692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06474112,"about_ca_system_score_gemma":0.1579893,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9960218,"about_ca_topic_score_gemma":0.9948014,"domain_scores_codex":[0.9952089,0.0003259372,0.0005818678,0.0005765336,0.002184127,0.001122608],"domain_scores_gemma":[0.9584126,0.001442392,0.001453736,0.001052942,0.03536816,0.002270123],"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":[0.0000286628,0.00000892041,0.001479389,0.0002653498,0.00002385095,0.000006968018,0.00002779793,0.0001011245,0.000007687117,0.0003463967,0.9960388,0.001665147],"study_design_scores_gemma":[0.0002593937,0.000023696,0.05147937,0.001489112,0.0001199877,0.00004110887,0.0008694796,0.0007122233,0.0002170567,0.0007931786,0.9438748,0.0001205874],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008022691,0.00006179776,0.00002391152,0.0001528931,0.00003217585,0.00002110347,0.9986927,0.0000550239,0.0008801268],"genre_scores_gemma":[0.001268229,0.0003975905,0.0004231132,0.0002241395,0.00002567319,0.0001760934,0.9923686,0.0001066994,0.005009862],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08219565,"threshold_uncertainty_score":0.4697319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04064528114805679,"score_gpt":0.2766803314600484,"score_spread":0.2360350503119916,"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."}}