{"id":"W4408823332","doi":"10.35833/mpce.2024.000264","title":"A Clearing Mechanism with Reduced Computational Complexity for Spot Flexibility Markets","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Université du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières","funders":"","keywords":"Clearing; Flexibility (engineering); Market clearing; Mechanism (biology); Spot market; Hot spot (computer programming); Computer science; Spot contract; Sweet spot; Computational complexity theory; Business; Operations research; Economics; Engineering; Simulation; Microeconomics; Futures contract; Algorithm; Finance; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002359277,0.0001113527,0.000282519,0.0001606076,0.0001954447,0.0003496122,0.0002243101,0.00005336422,0.00004710831],"category_scores_gemma":[0.00008193214,0.00007211758,0.0001179323,0.000193287,0.00009719164,0.0002853045,0.00003740573,0.0001125072,0.000003072815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000394396,"about_ca_system_score_gemma":0.00009423207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001239924,"about_ca_topic_score_gemma":0.0000101019,"domain_scores_codex":[0.9982052,0.0001425145,0.0006588581,0.0002746462,0.0005854445,0.0001333173],"domain_scores_gemma":[0.9984046,0.000556135,0.000322906,0.0001880749,0.0003968342,0.0001314311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003965051,0.00006394156,0.00001760835,0.00002466174,0.0001006111,0.00001061791,0.0005471394,0.01096744,0.0005213175,0.9509683,0.001898414,0.03448341],"study_design_scores_gemma":[0.0004014143,0.000219631,0.0007531375,0.0001140323,0.00002631486,0.0005707086,0.001248677,0.1841318,0.000293039,0.7928298,0.01927814,0.0001333339],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2030284,0.0003370019,0.7948901,0.0004316722,0.0004240149,0.00007891528,0.00001984077,0.00001913413,0.0007709497],"genre_scores_gemma":[0.9970562,0.000005997459,0.001725248,0.00005793649,0.0001237708,0.000006972931,0.000001454295,0.0000134932,0.001008925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7940278,"threshold_uncertainty_score":0.3371318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09144401574047728,"score_gpt":0.3474117659839384,"score_spread":0.2559677502434611,"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."}}