{"id":"W6939088965","doi":"10.6068/dp14ba9038cfb68","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, Unknown arrears owing at beginning of March of the fiscal year, Partial compliance with payment in March of the fiscal yearage of cases, Non-assigned payment, 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":"","field":"","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":[0.001629065,0.001188811,0.002247697,0.0001231578,0.0002249959,0.00011592,0.0008425578,0.0003197271,0.0002045891],"category_scores_gemma":[0.0001275535,0.0008765016,0.00000196332,0.0005276811,0.002235175,0.000325746,0.002013946,0.0008401739,6.233664e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001180477,"about_ca_system_score_gemma":0.006639373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9968228,"about_ca_topic_score_gemma":0.9831358,"domain_scores_codex":[0.9905468,0.001483564,0.001705792,0.001651764,0.002816281,0.001795751],"domain_scores_gemma":[0.9924985,0.001744089,0.002315004,0.002355366,0.0002545974,0.0008324873],"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":[0.005182073,0.0005381876,0.005820793,0.002641967,0.0009706272,0.0007291959,0.00003105555,0.0002976582,0.0002729367,0.00008114222,0.9832985,0.0001358478],"study_design_scores_gemma":[0.007020513,0.001268924,0.008260191,0.001126275,0.001164707,0.0008450619,0.0005357059,0.00399979,0.000007931634,1.605594e-7,0.9746559,0.001114886],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00643712,0.003095369,0.00001625363,0.000006415364,0.0001904733,0.003151059,0.9868748,0.00001475255,0.000213726],"genre_scores_gemma":[0.08508416,0.0005722037,0.0002323227,0.00003160332,0.00002712421,0.00007815788,0.9129282,0.0002344013,0.0008118136],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07864703,"threshold_uncertainty_score":0.9993685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0352977794840371,"score_gpt":0.2609809236685757,"score_spread":0.2256831441845386,"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."}}