{"id":"W6976529878","doi":"10.6068/dp15df28cd0cb58","title":"Trend 1980 - 2015. Energy Information Administration. International Energy Statistics: Electricity | Country: Canada | Category: Generation | Series: Nuclear Electricity Net Generation | Units: Btu, 1980-2015. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 004-015-003.","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"Utopian, Dystopian, and Speculative Fiction","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity generation; Electricity; Renewable energy; Energy policy; Energy (signal processing); Production (economics); Energy subsidies; 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":[],"consensus_categories":[],"category_scores_codex":[0.001323571,0.001851528,0.002107706,0.006337002,0.001833006,0.004327406,0.003469598,0.001295266,0.06247566],"category_scores_gemma":[0.01242713,0.001255108,0.001313456,0.0296376,0.0006056795,0.00290709,0.00177077,0.003088701,0.06625737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01715219,"about_ca_system_score_gemma":0.03800839,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9188095,"about_ca_topic_score_gemma":0.9091207,"domain_scores_codex":[0.9976978,0.0001480637,0.0002397496,0.0003572872,0.001079853,0.0004773026],"domain_scores_gemma":[0.9824705,0.0007665181,0.0006927281,0.000915202,0.01445572,0.0006993134],"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":[0.0000148212,0.000005904638,0.0005446481,0.0001396533,0.00001299928,0.000004030817,0.00000915779,0.000100766,0.000009770969,0.0003294783,0.9978963,0.0009324884],"study_design_scores_gemma":[0.00008651916,0.00000716199,0.01036063,0.0004183666,0.00002706533,0.00001250975,0.0001930816,0.0003040791,0.0001775456,0.0006480524,0.987725,0.0000399316],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003676367,0.00002621949,0.0000147573,0.00005438487,0.0000203504,0.000006343594,0.9992575,0.00004637407,0.0005372894],"genre_scores_gemma":[0.000269717,0.00007290598,0.0001015197,0.00003617809,0.000008780341,0.00003766712,0.9982493,0.0000427472,0.001181328],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08119047,"threshold_uncertainty_score":0.2090019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03484745918463035,"score_gpt":0.2458143695616692,"score_spread":0.2109669103770389,"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."}}