{"id":"W6920341888","doi":"10.6068/dp14ba8dffce238","title":"Trend 2006 - 2012. Statistics Canada. CANSIM: Children and Youth - Crime and Justice | Country: Canada | Table: Survey of Maintenance Enforcement Programs (SMEP), activity status, by type of beneficiary, interjurisdictional support order status and collection rates | Variable: Total all cases, Total interjurisdictional support order cases, Other payment collection rate, Spouse as the only beneficiary | Units: Rate, 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":"Descriptive statistics; Economic Justice; Census; Criminal justice; Law enforcement; Socioeconomic status; Population; Official statistics; Population statistics; Demographic statistics","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":[0.002479625,0.002566791,0.003050844,0.009636473,0.003522379,0.004600785,0.005838295,0.001440607,0.08347867],"category_scores_gemma":[0.01953266,0.002222094,0.002505849,0.04203011,0.0006325675,0.002541933,0.002472016,0.003240758,0.03924077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06675939,"about_ca_system_score_gemma":0.1637031,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9964007,"about_ca_topic_score_gemma":0.9949834,"domain_scores_codex":[0.995065,0.0003147008,0.0006106379,0.000570901,0.002318743,0.001120058],"domain_scores_gemma":[0.9585447,0.001281559,0.001379436,0.0009612372,0.03566611,0.002166965],"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":[0.0000302655,0.000009670427,0.001698044,0.0002949036,0.00002829216,0.000006466415,0.00002903848,0.000105492,0.000008538502,0.0003552182,0.9957179,0.001716222],"study_design_scores_gemma":[0.0002819358,0.00002603508,0.0590837,0.001449697,0.0001431329,0.00004230301,0.0009073406,0.0007187666,0.0002516049,0.0006864981,0.9362799,0.0001291164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008017963,0.00005512032,0.00002287577,0.0001420361,0.00003069716,0.00002326246,0.9986877,0.00005678223,0.0009014026],"genre_scores_gemma":[0.001217082,0.0003766463,0.0004345903,0.0002088706,0.00002394817,0.000184903,0.9927114,0.0001075399,0.004735033],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08347867,"threshold_uncertainty_score":0.4843755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02438079845391935,"score_gpt":0.263500037647431,"score_spread":0.2391192391935117,"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."}}