{"id":"W6958025262","doi":"10.6068/dp14ba88f981d23","title":"Trend 1990 - 2001. Statistics Canada. CANSIM: International Trade - Service Imports | Country: Canada | Table: International transactions in services, commercial services by industry | Variable: Receipts, Other financial services (x 1,000,000), Machinery and transportation equipment | Units: $CAD, 1990-2001. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-133.","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; Service (business); Goods and services; Official statistics; Census; International comparisons; Summary statistics; National accounts; Financial services","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001890524,0.002472971,0.002652059,0.008704041,0.003378088,0.004955833,0.004916406,0.001469321,0.09226567],"category_scores_gemma":[0.01601028,0.00174175,0.001998469,0.04165721,0.0006041955,0.002648451,0.002181688,0.003139884,0.05880389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04701686,"about_ca_system_score_gemma":0.125435,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939834,"about_ca_topic_score_gemma":0.9917656,"domain_scores_codex":[0.9960681,0.0002241991,0.0004049146,0.0005295518,0.001846661,0.0009265917],"domain_scores_gemma":[0.9696183,0.0009535906,0.0009501655,0.0008842085,0.02619115,0.001402635],"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":[0.00002406673,0.000006315125,0.0009845609,0.0002344507,0.00001958193,0.000007182529,0.00001875115,0.0001005742,0.0000079973,0.0003366978,0.9967284,0.001531388],"study_design_scores_gemma":[0.0001499201,0.00001250138,0.02310552,0.0008775,0.00007014717,0.00002893896,0.0004399131,0.0004560186,0.0001673905,0.0005828791,0.97403,0.00007929824],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005172196,0.00004900118,0.00001885303,0.0001016052,0.00002474231,0.00001098293,0.9988667,0.00005019705,0.0008262671],"genre_scores_gemma":[0.0007370003,0.0002724104,0.0002960853,0.0001278657,0.0000159104,0.00008972116,0.9944715,0.00009973358,0.003889629],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9077343,"threshold_uncertainty_score":0.3411328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940544127896444,"score_gpt":0.2496952385271576,"score_spread":0.2302897972481932,"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."}}