{"id":"W6938871809","doi":"10.6068/dp14ba827a98e9","title":"Trend 1992 - 1999. Statistics Canada. CANSIM: International Trade - Trade Patterns | Country: Canada | Table: Interprovincial and international trade flows at producer prices | Variable: Primary metal products (x 1,000,000), International imports | Units: $CAD, 1992-1999. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-134.","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; Census; Official statistics; International comparisons; Summary statistics; Trade barrier; Statistical analysis; Economic integration; China","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":[0.001583258,0.002306414,0.002319843,0.008987556,0.003199624,0.004890859,0.004421769,0.001319171,0.09932846],"category_scores_gemma":[0.01339345,0.001645088,0.001770763,0.04411955,0.0005873437,0.002613444,0.002131294,0.002710072,0.06108779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05006256,"about_ca_system_score_gemma":0.1275542,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.993959,"about_ca_topic_score_gemma":0.9917263,"domain_scores_codex":[0.9963312,0.0001982153,0.0003603736,0.0004382402,0.001777886,0.0008941881],"domain_scores_gemma":[0.9719605,0.000762561,0.0008446773,0.0007431707,0.02448546,0.001203713],"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":[0.00002093105,0.000005869253,0.0009811636,0.0002077806,0.00001672119,0.000007537348,0.0000188807,0.0001028813,0.000008606001,0.0004283272,0.9965108,0.001690554],"study_design_scores_gemma":[0.000104368,0.00001022871,0.02187624,0.0007047003,0.00005113658,0.00002557655,0.0004613076,0.0004143972,0.0001614098,0.0006190544,0.9755036,0.00006807825],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005740175,0.00004669671,0.00002358258,0.0001031218,0.00002724195,0.0000144138,0.9983491,0.00005738521,0.001321102],"genre_scores_gemma":[0.0008991655,0.0003108529,0.0003842964,0.0001196814,0.00001603466,0.0001035392,0.9922713,0.0001072403,0.005787842],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09932846,"threshold_uncertainty_score":0.3632311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992977902536337,"score_gpt":0.2415423716683598,"score_spread":0.2216125926429964,"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."}}