{"id":"W6920339072","doi":"10.6068/dp14ba8acdc2e10","title":"Trend 1997 - 2006. Statistics Canada. CANSIM: International Trade - Merchandise Exports | Country: Canada | Table: Merchandise imports and exports customs-based price indexes and United States trade, and Standard International Trade Classification (SITC revision 3) price indexes for all countries and United States | Variable: Exports, Major group 4.11 Petroleum and coal products, United States, Paasche current weighted | Units: 1997=100, 1997-2006. 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":"Official statistics; Economic statistics; Summary statistics; Price index; Census; International comparisons; Statistical analysis; International Standard Industrial Classification; Publication","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":[0.001193051,0.002519258,0.002410058,0.008863769,0.002540183,0.004722337,0.004008349,0.00128148,0.07385287],"category_scores_gemma":[0.01172601,0.001360098,0.001777971,0.04040713,0.0005994153,0.002264805,0.001849266,0.002872508,0.0572261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03086786,"about_ca_system_score_gemma":0.08050958,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9868937,"about_ca_topic_score_gemma":0.9849173,"domain_scores_codex":[0.9972698,0.0001379119,0.0002758857,0.0004100727,0.001269028,0.0006371752],"domain_scores_gemma":[0.9809991,0.0007213726,0.0007819672,0.0006221554,0.01603062,0.0008446874],"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":[0.00002110489,0.000005257082,0.0008452793,0.00021603,0.00001859189,0.000007418497,0.00001309188,0.0001086379,0.00000920295,0.0003334159,0.9972638,0.001158241],"study_design_scores_gemma":[0.0001140057,0.000008336447,0.01546836,0.0006702859,0.00004691266,0.00002451494,0.0002974788,0.0003678804,0.0001720701,0.0005225927,0.9822498,0.00005768029],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004578021,0.00004361569,0.00001367329,0.00005929521,0.00001994217,0.000006175551,0.9991161,0.00004128146,0.0006541795],"genre_scores_gemma":[0.0004567322,0.0001724216,0.0001538457,0.0000645429,0.00001086912,0.00004118866,0.9968519,0.0000519491,0.002196542],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07385287,"threshold_uncertainty_score":0.2470624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02239541367861308,"score_gpt":0.2579396155518011,"score_spread":0.235544201873188,"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."}}