{"id":"W3126085421","doi":"10.2139/ssrn.3198117","title":"Strategic Use of Storage: The Impact of Carbon Policy, Resource Availability, and Technology Efficiency on a Renewable-Thermal Power System","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Electric Power System Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Carbon capture and storage (timeline); Environmental economics; Renewable energy; Incentive; Business; Carbon tax; Thermal energy storage; Industrial organization; Energy storage; Renewable resource; Profit (economics); Marginal value; Natural resource economics; Economics; Greenhouse gas; Microeconomics; Climate change; Power (physics); Engineering","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":[0.001704991,0.0004603812,0.0008381447,0.0005210333,0.0005743579,0.003040547,0.0008298371,0.00128121,0.004753977],"category_scores_gemma":[0.004259937,0.0003701806,0.0005400219,0.0008464862,0.000812401,0.002112792,0.001064142,0.001117577,0.0002609768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001985367,"about_ca_system_score_gemma":0.002675882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01088781,"about_ca_topic_score_gemma":0.02607067,"domain_scores_codex":[0.9992784,0.0003207968,0.00004242726,0.00005980658,0.0001051139,0.0001935805],"domain_scores_gemma":[0.9962997,0.00209546,0.000515104,0.0001120692,0.0005815233,0.000396255],"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":[0.003802486,0.0009592276,0.09024175,0.0005444256,0.0007076011,0.002065266,0.0002959448,0.7532738,0.0130379,0.1048458,0.004179615,0.02604603],"study_design_scores_gemma":[0.000507659,0.0021876,0.1067142,0.0001157076,0.0009683148,0.0006018069,0.005058543,0.748833,0.01311197,0.1163366,0.00534283,0.0002216242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792436,0.0005619341,0.002113636,0.002264526,0.00005268233,0.00002386919,0.00038723,0.00003454086,0.01531809],"genre_scores_gemma":[0.9994093,0.00007524723,0.00007654738,0.00002206622,0.000003880152,0.000001796464,0.00002863961,0.000002445804,0.0003800771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01088781,"threshold_uncertainty_score":0.02164888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007470031320176298,"score_gpt":0.2212708062700971,"score_spread":0.2138007749499208,"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."}}