{"id":"W6976713689","doi":"10.6068/dp14ba8929a4e47","title":"Trend 1990 - 2001. Statistics Canada. CANSIM: International Trade - Service Imports | Country: Canada | Table: International transactions in services, commercial services by industry | Variable: Receipts, Non-financial commissions (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":"Official statistics; Economic statistics; Service (business); Goods and services; Census; International comparisons; Summary statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00195738,0.002527894,0.002669328,0.008946533,0.003405545,0.005041468,0.004886078,0.001460391,0.09636761],"category_scores_gemma":[0.01686092,0.001824928,0.002026047,0.0432548,0.0005970536,0.002724932,0.002203554,0.003139123,0.06215366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04710196,"about_ca_system_score_gemma":0.1259997,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9936665,"about_ca_topic_score_gemma":0.9912288,"domain_scores_codex":[0.9959253,0.0002306385,0.0004305427,0.0005418809,0.001937421,0.0009342409],"domain_scores_gemma":[0.9670628,0.001025302,0.0009808524,0.0009352979,0.02852445,0.001471315],"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":[0.00002339388,0.000006093213,0.0009277037,0.0002318958,0.00001830835,0.000006912493,0.00001819186,0.00009596915,0.000007915031,0.000326959,0.9968285,0.001508031],"study_design_scores_gemma":[0.0001463737,0.00001232519,0.02313875,0.0008602299,0.00006747905,0.00002737223,0.0004180233,0.0004301833,0.0001639645,0.0005701998,0.9740868,0.00007822468],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004929288,0.00004627658,0.00001912033,0.00009723043,0.0000248863,0.00001156803,0.9988376,0.00005242918,0.0008614225],"genre_scores_gemma":[0.0006714165,0.0002569577,0.0002948974,0.000121115,0.00001549287,0.0000919203,0.9945186,0.0001034805,0.003926185],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09636761,"threshold_uncertainty_score":0.3417503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02003765516119842,"score_gpt":0.254871725102141,"score_spread":0.2348340699409426,"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."}}