{"id":"W6901558855","doi":"10.6068/dp14ba82b2d6c51","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: Sexual assault centres, Claims assistance, Number | 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; Economic statistics; Summary statistics; Census","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":[0.002391327,0.002514649,0.003024105,0.009527533,0.003638022,0.005632828,0.005434505,0.001564512,0.102426],"category_scores_gemma":[0.01965784,0.002230699,0.002448049,0.04112171,0.0006735897,0.002934759,0.002796249,0.003302545,0.05755925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06907913,"about_ca_system_score_gemma":0.1770992,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9962048,"about_ca_topic_score_gemma":0.9944521,"domain_scores_codex":[0.9949974,0.0003125225,0.0005511736,0.0005618976,0.002383791,0.001193204],"domain_scores_gemma":[0.9597893,0.001192489,0.001182606,0.0010105,0.03464488,0.002180247],"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":[0.00002660723,0.000007576994,0.001061684,0.000257608,0.0000214239,0.000006519641,0.00002394627,0.0000928502,0.000008967201,0.0003589182,0.9962495,0.001884361],"study_design_scores_gemma":[0.0001858864,0.00001770619,0.0306733,0.001070693,0.00009412127,0.00003405084,0.0006929291,0.0005897918,0.0002105923,0.0006765925,0.9656471,0.0001073399],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006746454,0.00007351399,0.00002946594,0.0001843194,0.00004353766,0.0000230246,0.9982451,0.00008346712,0.001250031],"genre_scores_gemma":[0.001244858,0.0005078336,0.0005522207,0.0002587123,0.000029318,0.0001776295,0.9899651,0.0001801118,0.00708421],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.102426,"threshold_uncertainty_score":0.5012065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02245041294406819,"score_gpt":0.2429085774560826,"score_spread":0.2204581645120144,"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."}}