{"id":"W6939202550","doi":"10.6068/dp14ba8cc19ea35","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 for the entire fiscal year, by activity status, type of beneficiary, change in arrears, length of enrolment | Variable: Total all cases, Total change in arrears status, Enrolled for more than 10 years, Unknown beneficiary | 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":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arrears; Economic statistics; Law enforcement; Enforcement; Economic Justice; Payment; Beneficiary; Official statistics; Descriptive 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":[0.002577561,0.002543678,0.00300011,0.009401498,0.003444189,0.004757793,0.005619768,0.001513812,0.08596433],"category_scores_gemma":[0.02210619,0.002123094,0.002296929,0.03919493,0.0006489157,0.002516024,0.002486269,0.003281746,0.04135273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06566843,"about_ca_system_score_gemma":0.1634381,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9960333,"about_ca_topic_score_gemma":0.9948624,"domain_scores_codex":[0.9950537,0.0003360196,0.000615192,0.0005941787,0.002312523,0.001088514],"domain_scores_gemma":[0.9543661,0.001519332,0.001535142,0.001116716,0.03907489,0.002387853],"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":[0.00003002813,0.000009426009,0.001513191,0.0002741582,0.00002511158,0.000006669929,0.00002599241,0.0001037596,0.000008450507,0.000318711,0.9959769,0.001707618],"study_design_scores_gemma":[0.0002968455,0.00002590178,0.05473585,0.001484012,0.0001261397,0.00004109264,0.0008172516,0.0007448729,0.0002283511,0.0007786955,0.9405949,0.0001259423],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008109427,0.00005657444,0.00002452155,0.0001515308,0.00003308378,0.00002414867,0.9986828,0.00006004047,0.0008862152],"genre_scores_gemma":[0.001234365,0.0003655152,0.0004547803,0.0002288981,0.00002652706,0.0001906025,0.9924554,0.0001130467,0.004930844],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08596433,"threshold_uncertainty_score":0.47646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04942057806057287,"score_gpt":0.2674101937376521,"score_spread":0.2179896156770793,"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."}}