{"id":"W6976646796","doi":"10.6068/dp15e6e54e07967","title":"Trend 1980 - 2014. Energy Information Administration. International Energy Statistics: Petroleum | Country: Canada | Category: Production | Series: Refinery Output of Kerosene | 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; Production (economics); Kerosene; Energy policy; Energy (signal processing); Refinery; Agency (philosophy); 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":[0.001273265,0.00201204,0.002200789,0.007113874,0.001661982,0.004054921,0.003476471,0.001252149,0.05440886],"category_scores_gemma":[0.01065485,0.00139041,0.001392676,0.03217511,0.000578213,0.00288097,0.001721277,0.002987588,0.05664552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01668917,"about_ca_system_score_gemma":0.03766736,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9092546,"about_ca_topic_score_gemma":0.8893017,"domain_scores_codex":[0.9977341,0.0001246548,0.0002323882,0.0003370859,0.001126428,0.0004453422],"domain_scores_gemma":[0.9832165,0.0006798104,0.0007084958,0.0007890738,0.01399643,0.0006096559],"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":[0.00002034739,0.000008082195,0.0007961693,0.000202386,0.00001870035,0.000005211076,0.000009481069,0.0001376731,0.00001440366,0.0003749374,0.9971651,0.001247394],"study_design_scores_gemma":[0.00008964404,0.000008003812,0.01310762,0.0004286621,0.00003177516,0.00001286465,0.0001843414,0.0003054921,0.0002192942,0.0005749622,0.9849973,0.00004006909],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004258103,0.00002789245,0.00001490533,0.00004962319,0.00001910667,0.000006442835,0.9992446,0.00004157501,0.0005533181],"genre_scores_gemma":[0.0002733809,0.0000882377,0.0000995103,0.00003037206,0.000008029473,0.00003623907,0.9982218,0.00003598945,0.001206424],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09074545,"threshold_uncertainty_score":0.1825597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02172016001357583,"score_gpt":0.2490512552317245,"score_spread":0.2273310952181487,"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."}}