{"id":"W6976227874","doi":"10.6068/dp14ba8dad65192","title":"Trend 1997 - 2008. Statistics Canada. CANSIM: International Trade - Merchandise Exports | Country: Canada | Table: Interprovincial and international trade flows at producer prices | Variable: Non-market services provided by non-profit institutions serving households (x 1,000,000), Total supply and total demand | Units: $CAD, 1997-2008. 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":"Economic statistics; Official statistics; Goods and services; Summary statistics; Census; International comparisons; Descriptive statistics; Statistical analysis; National accounts","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.00100516,0.001677939,0.001567431,0.0003260992,0.0004981446,0.0009916954,0.003118081,0.0007588732,0.003234679],"category_scores_gemma":[0.0001604257,0.001675172,9.056089e-7,0.0005585117,0.0004952098,0.001661451,0.002406424,0.001320375,0.00001523489],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001237835,"about_ca_system_score_gemma":0.01395847,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9980013,"about_ca_topic_score_gemma":0.998279,"domain_scores_codex":[0.9910762,0.0003847606,0.001794932,0.002841518,0.002493681,0.001408883],"domain_scores_gemma":[0.9941409,0.0005615209,0.001501731,0.002426749,0.00007690075,0.001292216],"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":[0.00072549,0.0002106117,0.0002543478,0.001192737,0.00125238,0.001122028,0.00003947658,0.00006717182,0.00005146498,0.00006638504,0.9948531,0.0001648513],"study_design_scores_gemma":[0.002388056,0.0001204333,0.00008520873,0.000259655,0.0008696533,0.001560872,0.0003408973,0.0253225,4.381837e-7,1.981679e-7,0.9672913,0.001760781],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004670351,0.002019332,0.00001727499,0.00003553167,0.002641697,0.001955764,0.9912552,0.0001781563,0.001850306],"genre_scores_gemma":[0.0008219331,0.0006273597,0.0004106075,0.0003141069,0.0009294613,0.0001421489,0.9941129,0.000593755,0.002047729],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02756174,"threshold_uncertainty_score":0.9995967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01602881152604085,"score_gpt":0.2392821817239804,"score_spread":0.2232533701979396,"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."}}