{"id":"W6938930008","doi":"10.6068/dp14ba7f8ae1d77","title":"Trend 1998 - 2000. Statistics Canada. CANSIM: Crime and Justice - Victims and Victimization | Country: Canada | Table: Requests for services received by shelters from ex-residents and non-residents, snapshot day | Variable: Requests for other services | Units: , 1998-2000. 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; Census; Official statistics; Criminal justice; Law enforcement; Economic statistics; Summary statistics; Social statistics; Snapshot (computer storage)","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":[0.002335617,0.002514929,0.002807094,0.009272011,0.003495009,0.005359223,0.005487211,0.001498201,0.1065524],"category_scores_gemma":[0.0192268,0.002225912,0.00225211,0.04037463,0.000677827,0.002823804,0.002623455,0.003185332,0.05933657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06664455,"about_ca_system_score_gemma":0.1697039,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958854,"about_ca_topic_score_gemma":0.9934628,"domain_scores_codex":[0.9951933,0.0002856789,0.0005185859,0.0005253622,0.002326114,0.001150929],"domain_scores_gemma":[0.961937,0.001137947,0.001138356,0.0009866366,0.03276293,0.002037151],"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":[0.00002717243,0.000007254483,0.0009833327,0.0002271701,0.0000186397,0.000006036225,0.00002173026,0.00009315105,0.000008201981,0.0003570813,0.9964131,0.001837171],"study_design_scores_gemma":[0.0001850378,0.00001641411,0.02829656,0.0009008407,0.00007560219,0.00002968309,0.0005977239,0.000560037,0.0002025469,0.0006530276,0.9683862,0.00009625385],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000643589,0.00005998206,0.00002816826,0.0001750152,0.00004009462,0.00002326108,0.9981508,0.0000880334,0.001370247],"genre_scores_gemma":[0.00121031,0.0004317877,0.000514384,0.0002351384,0.00002678604,0.000184559,0.9901801,0.0001886181,0.007028157],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1065524,"threshold_uncertainty_score":0.4835423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01835633381533172,"score_gpt":0.2565159820753239,"score_spread":0.2381596482599922,"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."}}