{"id":"W6976721810","doi":"10.6068/dp14ba9044b8945","title":"Trend 2006 - 2012. Statistics Canada. CANSIM: Crime and Justice - Civil Courts and Family Law | Country: Canada | Table: Survey of Maintenance Enforcement Programs (SMEP), enrolled cases, by activity status, compliance with regular and total payments, arrears status and assignment status at March 31 | Variable: Total all cases, No arrears owing at beginning of March of the fiscal year, Partial compliance with payment in March of the fiscal yearage of cases, Unknown payment assignment status, Total payment due | 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":"Engineering and Materials Science Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arrears; Payment; Law enforcement; Enforcement; Economic statistics; Economic Justice; Census; Alimony","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":[0.0007833825,0.0006731162,0.001256069,0.0000589653,0.0001201956,0.00006362767,0.0003968009,0.00015111,0.00007559964],"category_scores_gemma":[0.00005828241,0.0004867829,0.000001196504,0.0002129042,0.0008821291,0.0001663167,0.0009537325,0.0004007741,1.671386e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006319831,"about_ca_system_score_gemma":0.001748513,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9834433,"about_ca_topic_score_gemma":0.8912496,"domain_scores_codex":[0.9952878,0.0003921259,0.0009396646,0.0008109772,0.001446005,0.001123396],"domain_scores_gemma":[0.9970119,0.0006879069,0.000666091,0.001094775,0.000113285,0.000426033],"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":[0.0008777098,0.0001586408,0.00139573,0.002522668,0.0004909281,0.000194412,0.00003345466,0.002556191,0.0003611115,0.00006800819,0.9912365,0.0001046218],"study_design_scores_gemma":[0.002719799,0.0006765862,0.0044011,0.0007784026,0.0004516939,0.0002230398,0.0003848276,0.005756131,0.00001262166,1.131955e-7,0.9838927,0.0007029175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005833808,0.003437039,0.00003810091,0.000003903027,0.0002800614,0.001365707,0.9888684,0.00001395424,0.0001590781],"genre_scores_gemma":[0.1065585,0.001612711,0.0003080213,0.00001527296,0.0000250189,0.00005759879,0.8908075,0.0001096092,0.0005057628],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1007247,"threshold_uncertainty_score":0.9997584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02646724793874517,"score_gpt":0.2373573068271175,"score_spread":0.2108900588883723,"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."}}