{"id":"W6977108038","doi":"10.6068/dp14ba88da0cd9","title":"Trend 1992 - 2000. Statistics Canada. CANSIM: International Trade - Merchandise Exports | Country: Canada | Table: Merchandise imports and exports customs-based price indexes and United States trade, and Standard International Trade Classification (SITC revision 3) price indexes for all countries and United States | Variable: Section V exports - end products, inedible, United States, Paasche current weighted | Units: 1992=100, 1992-2000. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-130.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Official statistics; Price index; Census; Economic statistics; Summary statistics; International comparisons; International Standard Industrial Classification; Publication; 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":[0.001223792,0.00249276,0.00230232,0.009172946,0.002443953,0.004745839,0.004028714,0.001308492,0.07479162],"category_scores_gemma":[0.01189466,0.001371821,0.001693835,0.04224186,0.0005807901,0.002308811,0.001786832,0.002851768,0.05850943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03176705,"about_ca_system_score_gemma":0.07765824,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.987321,"about_ca_topic_score_gemma":0.9848203,"domain_scores_codex":[0.9972749,0.0001328946,0.0002665773,0.0004153584,0.001262868,0.0006473656],"domain_scores_gemma":[0.9809537,0.0006887775,0.0008266387,0.0005935995,0.01607968,0.0008575634],"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":[0.00002147418,0.000005638088,0.0009512824,0.0002166016,0.00001884304,0.000007372765,0.00001389049,0.0001105822,0.000008937754,0.0003336182,0.9970944,0.001217434],"study_design_scores_gemma":[0.0001306988,0.00000946983,0.01951606,0.0006569668,0.00004973557,0.00002454477,0.0003310059,0.0003917047,0.0001711756,0.0005204214,0.9781377,0.00006047506],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000053254,0.00004351724,0.00001289287,0.00005984021,0.00001926067,0.00000657681,0.9990929,0.00004113844,0.0006706872],"genre_scores_gemma":[0.0004960272,0.0001588363,0.000141378,0.00006355048,0.00001069202,0.00004311152,0.9966937,0.00004908876,0.002343541],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07479162,"threshold_uncertainty_score":0.2502028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02593257781141787,"score_gpt":0.2641542652103517,"score_spread":0.2382216873989338,"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."}}