{"id":"W6957849581","doi":"10.6068/dp14ba8fd971731","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, Non-interjurisdictional support orderage 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; Economic Justice; Beneficiary; 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":[0.002193086,0.00241414,0.002885027,0.01020381,0.003485776,0.004739297,0.005605952,0.00146625,0.08495867],"category_scores_gemma":[0.01994232,0.002048752,0.002161493,0.040005,0.0006241115,0.002401316,0.002418727,0.003121044,0.03750649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06592364,"about_ca_system_score_gemma":0.1511377,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961719,"about_ca_topic_score_gemma":0.995265,"domain_scores_codex":[0.9955468,0.0002601023,0.000557351,0.0005385938,0.002068215,0.001028966],"domain_scores_gemma":[0.9589586,0.001351159,0.00147976,0.0009413297,0.0350459,0.002223375],"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":[0.00002728883,0.000009339241,0.001717031,0.0002899535,0.0000245832,0.000007367165,0.00003045857,0.00009983361,0.000008003269,0.0003537033,0.9956475,0.001785037],"study_design_scores_gemma":[0.0002667233,0.00002526006,0.06479792,0.001643531,0.0001358444,0.00004851364,0.001012299,0.0007567512,0.0002379872,0.0007936525,0.930154,0.0001274972],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009268265,0.00006164588,0.00002187535,0.0001403971,0.0000299105,0.00002170634,0.9986697,0.00005284521,0.0009092699],"genre_scores_gemma":[0.001365837,0.0004044284,0.0003822939,0.0002080971,0.00002455495,0.0001691493,0.9923393,0.0000964227,0.005009914],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08495867,"threshold_uncertainty_score":0.4783117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05326889922558666,"score_gpt":0.2912139759460156,"score_spread":0.2379450767204289,"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."}}