{"id":"W6957901489","doi":"10.6068/dp15e7320105e57","title":"Trend 1980 - 2014. Energy Information Administration. International Energy Statistics: Petroleum | Country: Canada | Category: Consumption | Series: Consumption Residual Fuel Oil | Units: Barrels Per Day, 1980-2014. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 004-015-006.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Petroleum; Energy consumption; Consumption (sociology); Energy policy; Energy (signal processing); Agency (philosophy); Production (economics); Administration (probate law); Energy security","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":[0.001170206,0.00189415,0.002039087,0.006589378,0.001533013,0.003637447,0.003267705,0.00119261,0.05121212],"category_scores_gemma":[0.01042747,0.00127926,0.001319751,0.030189,0.0005290547,0.002711185,0.001584269,0.002890851,0.05474787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01533722,"about_ca_system_score_gemma":0.03374679,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9080645,"about_ca_topic_score_gemma":0.8889741,"domain_scores_codex":[0.997983,0.0001154223,0.0001990019,0.0003020504,0.0009922819,0.0004081604],"domain_scores_gemma":[0.9852558,0.0005889385,0.0006150004,0.0006914454,0.01231143,0.0005374447],"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":[0.0000197296,0.000007683852,0.0007751345,0.00018631,0.00001740505,0.000004966825,0.000009452716,0.0001273963,0.00001332709,0.0003506264,0.9972284,0.001259559],"study_design_scores_gemma":[0.00009146458,0.000008460564,0.01416514,0.0004191473,0.0000338971,0.00001375078,0.000185084,0.0003158272,0.0002186541,0.0005713792,0.9839379,0.00003924576],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004647466,0.00002875546,0.00001542405,0.00004686539,0.00001914,0.000006470691,0.9992691,0.00004335147,0.00052456],"genre_scores_gemma":[0.0002826988,0.00008072675,0.0001024324,0.00002851967,0.000007924507,0.00003548873,0.99826,0.0000343744,0.001167819],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09193552,"threshold_uncertainty_score":0.1849538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02747574414138691,"score_gpt":0.2658661587900797,"score_spread":0.2383904146486928,"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."}}