{"id":"W2616747199","doi":"10.2118/185579-ms","title":"Assessing the Long-Term Energy Landscape Using a Global Energy Market Model","year":2017,"lang":"en","type":"article","venue":"SPE Latin America and Caribbean Petroleum Engineering Conference","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Energy mix; Fossil fuel; Renewable energy; Resource (disambiguation); Term (time); Primary energy; Market share; Energy market; Alternative energy; Energy (signal processing); Environmental economics; Population; Econometrics; Economics; Natural resource economics; Computer science; Engineering; Mathematics; Statistics; Electricity generation; Waste management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00112073,0.0008112125,0.0005448504,0.0008491562,0.0003475863,0.001527538,0.0008892196,0.001585147,0.003213355],"category_scores_gemma":[0.001971189,0.0003570906,0.001041637,0.001065824,0.0003743469,0.002084546,0.0007187291,0.000738329,0.0003642289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454658,"about_ca_system_score_gemma":0.0005928122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02134778,"about_ca_topic_score_gemma":0.01123178,"domain_scores_codex":[0.9997591,0.0001233991,0.000009856883,0.00004659218,0.00002905311,0.00003186912],"domain_scores_gemma":[0.9993185,0.0004452906,0.00008198778,0.00003873383,0.00007730061,0.00003820524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001354637,0.000009241972,0.002029051,0.00000963556,0.00001806673,0.00002773942,0.000007234245,0.9951658,0.00009447556,0.001737566,0.0001045536,0.0007830746],"study_design_scores_gemma":[0.000004018681,0.00001662634,0.0008935884,0.000003807609,0.0000056077,0.000008953442,0.00002310999,0.9972057,0.00005693296,0.001521154,0.0002545353,0.000006030982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9097452,0.0003449972,0.07027853,0.0008143368,0.00004120825,0.00006242903,0.002473691,0.000232087,0.01600759],"genre_scores_gemma":[0.9894873,0.0001155491,0.007995081,0.00005755456,0.00001008546,0.00005113544,0.000903766,0.00004748245,0.001331955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02134778,"threshold_uncertainty_score":0.04244709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02126093955595241,"score_gpt":0.2835546159618699,"score_spread":0.2622936764059175,"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."}}