{"id":"W6957683208","doi":"10.6068/dp14ba8fe457e0","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 active cases, Interjurisdictional support order-inage of cases, Unknown regularity of compliance in the fiscal year, Total cases, type of beneficiary cases | 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; Economic statistics; Beneficiary; Economic Justice; Census; Official statistics; Socioeconomic status; 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":[0.00217778,0.002427092,0.002908391,0.01019786,0.003494944,0.004786303,0.005623443,0.001467195,0.08521426],"category_scores_gemma":[0.01982052,0.002051865,0.002171745,0.04016428,0.0006244364,0.002414485,0.002430972,0.003134714,0.03792057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06526476,"about_ca_system_score_gemma":0.1501237,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961501,"about_ca_topic_score_gemma":0.9952195,"domain_scores_codex":[0.9955834,0.0002598282,0.0005574693,0.0005363564,0.002040842,0.001022109],"domain_scores_gemma":[0.9592056,0.001341615,0.001470728,0.0009362731,0.03484054,0.002205293],"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":[0.0000270831,0.000009247969,0.001699455,0.0002915019,0.00002474437,0.000007310397,0.0000304239,0.00009923775,0.000007877265,0.0003535414,0.995672,0.001777629],"study_design_scores_gemma":[0.00026761,0.00002515422,0.06416436,0.001646186,0.0001363083,0.00004831169,0.001013917,0.0007583366,0.0002364268,0.0007970369,0.9307787,0.000127642],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009074116,0.00006143221,0.00002153081,0.0001382908,0.00002960769,0.00002118152,0.9986871,0.00005215952,0.0008978656],"genre_scores_gemma":[0.001338863,0.0004019287,0.0003740746,0.0002035129,0.00002438934,0.0001663142,0.9925156,0.00009539931,0.004879903],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08521426,"threshold_uncertainty_score":0.4735312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05366280006199869,"score_gpt":0.2905534143438913,"score_spread":0.2368906142818926,"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."}}