{"id":"W6920351897","doi":"10.6068/dp14ba81fdde964","title":"Trend 2002 - 2010. Statistics Canada. CANSIM: Crime and Justice - Victims and Victimization | Country: Canada | Table: Victim services survey, types of services offered directly by victim service agencies | Variable: Court-based agencies, Compensation, financial | Units: # %, 2002-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-045.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crime statistics; Law enforcement; Official statistics; Criminal justice; Economic Justice; Census; Economic statistics; Service (business)","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":[0.002360028,0.002546528,0.002984395,0.009609388,0.003653186,0.005600293,0.005490371,0.00157002,0.1021786],"category_scores_gemma":[0.0193933,0.002256855,0.002431485,0.04171674,0.0006708883,0.002951666,0.002783145,0.003302261,0.05809059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06902651,"about_ca_system_score_gemma":0.1764824,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961798,"about_ca_topic_score_gemma":0.9944324,"domain_scores_codex":[0.9950245,0.0003022247,0.0005311176,0.0005576356,0.002390936,0.001193501],"domain_scores_gemma":[0.9597399,0.001161247,0.001158482,0.00100308,0.03476904,0.002168161],"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":[0.00002616302,0.000007642959,0.001024432,0.000252362,0.00002052729,0.000006287657,0.00002342243,0.00009135049,0.000009087099,0.0003543364,0.9963648,0.001819563],"study_design_scores_gemma":[0.0001849735,0.00001757346,0.03028548,0.001023556,0.00009148361,0.0000324454,0.0006914461,0.0005614953,0.0002164282,0.0006546227,0.9661352,0.0001051562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006602962,0.00006956973,0.00002851871,0.0001758877,0.00004235753,0.00002255144,0.9982728,0.00008170961,0.001240575],"genre_scores_gemma":[0.001197671,0.0004789121,0.0005282216,0.0002438814,0.00002823189,0.0001738746,0.9901904,0.0001748122,0.006984008],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1021786,"threshold_uncertainty_score":0.5008247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02502681814262469,"score_gpt":0.2344187589029025,"score_spread":0.2093919407602778,"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."}}