{"id":"W6976492770","doi":"10.6068/dp15e6e45afbd25","title":"Trend 1980 - 2014. Energy Information Administration. International Energy Statistics: Petroleum | Country: Canada | Category: Consumption | Series: Consumption of Other Petroleum Products | 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; Production (economics); Energy (signal processing); Agency (philosophy); Administration (probate law)","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":[0.001192391,0.001920584,0.00211524,0.007015594,0.001627129,0.003833829,0.003384652,0.001184318,0.05225852],"category_scores_gemma":[0.01056429,0.001306244,0.001361401,0.03195678,0.0005532738,0.002678199,0.001628006,0.002944495,0.05255386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01732977,"about_ca_system_score_gemma":0.03751484,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.925478,"about_ca_topic_score_gemma":0.908963,"domain_scores_codex":[0.9978486,0.0001172218,0.0002106709,0.0003012009,0.001096065,0.0004262837],"domain_scores_gemma":[0.9839452,0.0006110992,0.0006384007,0.0006867821,0.01354077,0.0005776596],"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":[0.00002121218,0.00000859384,0.0008586996,0.0002029035,0.00001874064,0.000005236687,0.00001075214,0.000128637,0.00001369163,0.0003649868,0.9970244,0.001342258],"study_design_scores_gemma":[0.00009463031,0.00000885413,0.01572793,0.000444525,0.0000361444,0.00001392764,0.0002107562,0.000326661,0.0002257281,0.0005562841,0.982313,0.00004160798],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004933282,0.00002940518,0.00001488364,0.00004819467,0.00001940339,0.00000709948,0.9992381,0.00004201678,0.0005515609],"genre_scores_gemma":[0.0003066648,0.00008957651,0.000105183,0.00003014416,0.00000845237,0.00003768635,0.9981478,0.00003533794,0.001239164],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9477415,"threshold_uncertainty_score":0.1748222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02670676112195032,"score_gpt":0.261702036173753,"score_spread":0.2349952750518027,"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."}}