{"id":"W6901652001","doi":"10.6068/dp14ba8e213bc56","title":"Trend 2006 - 2012. Statistics Canada. CANSIM: Children and Youth - Crime and Justice | 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, Unknown arrears at beginning of fiscal year, Enrolled for 5 years or less, Total cases, type of beneficiary | Units: #, 2006-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-025.","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; Economic statistics; Census; Official statistics; Descriptive statistics; Economic Justice; Law enforcement; Population; Criminal justice","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":[0.001270495,0.0008513065,0.002129918,0.0001976734,0.0001031327,0.00005038638,0.0008762958,0.0004530712,0.0005279866],"category_scores_gemma":[0.0006308227,0.0007284256,0.000001803825,0.0004782588,0.0005488838,0.0002855569,0.0007523963,0.0004994437,0.000001293542],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003845703,"about_ca_system_score_gemma":0.006773002,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9991261,"about_ca_topic_score_gemma":0.9958234,"domain_scores_codex":[0.9946964,0.0005409536,0.00139881,0.001102992,0.001237751,0.001023107],"domain_scores_gemma":[0.9922419,0.003247925,0.002122415,0.001636321,0.0003751576,0.0003762828],"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":[0.00891346,0.0004782389,0.0007502019,0.001202611,0.001124986,0.00009250162,0.00003557743,0.00008800392,0.00002018116,0.000101062,0.9866404,0.0005528016],"study_design_scores_gemma":[0.005068639,0.0013674,0.001606701,0.0002780014,0.00220671,0.0001856827,0.0008557445,0.0022823,0.000001881661,1.079517e-7,0.9852682,0.0008786067],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002045132,0.004357803,0.000003714898,0.000001109387,0.0003464852,0.003158233,0.9900092,0.00001760325,0.00006064716],"genre_scores_gemma":[0.02419047,0.0009345955,0.0001774878,0.00001133946,0.00008902876,0.00005520734,0.9737687,0.0002729151,0.0005002361],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02214534,"threshold_uncertainty_score":0.9995167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.057091126588231,"score_gpt":0.2845255924759906,"score_spread":0.2274344658877596,"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."}}