{"id":"W6901550819","doi":"10.6068/dp14ba822c8e240","title":"Trend 1990 - 2011. Statistics Canada. CANSIM: International Trade - Service Exports | Country: Canada | Table: International transactions in services, by selected countries | Variable: Middle East (x 1,000,000), Commercial services, payments | Units: $CAD, 1990-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-132.","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; Census; Economic statistics; International comparisons; Service (business); Goods and services; Summary statistics; Payment","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":[0.00179982,0.002452082,0.002522918,0.00918676,0.003119323,0.005176306,0.004814507,0.001420229,0.1008493],"category_scores_gemma":[0.01593204,0.001617785,0.001933431,0.04431968,0.0006171069,0.002896599,0.002258812,0.002971274,0.06384066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0473232,"about_ca_system_score_gemma":0.1223589,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9926172,"about_ca_topic_score_gemma":0.9902021,"domain_scores_codex":[0.9960966,0.0002082094,0.0004101985,0.0004887627,0.001880005,0.0009163749],"domain_scores_gemma":[0.9690297,0.0009615756,0.001005107,0.000848176,0.0267261,0.001429372],"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":[0.00002087543,0.000005446164,0.0008654754,0.000222187,0.00001644249,0.000006268353,0.00001522834,0.00008834909,0.000007199749,0.0003404486,0.9969156,0.001496441],"study_design_scores_gemma":[0.0001227811,0.00001163882,0.02208597,0.0008548946,0.00005868308,0.00002665288,0.00040219,0.0004198466,0.0001647577,0.0005787711,0.9752,0.00007374995],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005047149,0.00005228366,0.00001773819,0.0001073854,0.00002620667,0.00001174454,0.9986973,0.00005157421,0.0009852962],"genre_scores_gemma":[0.0007024975,0.0003065979,0.0002654431,0.0001296181,0.00001796428,0.00008934521,0.9939454,0.0001023705,0.004440749],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1008493,"threshold_uncertainty_score":0.3433555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02272661340323062,"score_gpt":0.2375546489940001,"score_spread":0.2148280355907695,"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."}}