{"id":"W1977963540","doi":"10.1016/j.procs.2013.06.095","title":"Compressed Air Storage and Wind Energy for Time-of-day Electricity Markets","year":2013,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Compressed air energy storage; Electricity; Energy storage; Renewable energy; Pumped-storage hydroelectricity; Wind power; Tariff; Computer science; Environmental economics; Automotive engineering; Environmental science; Distributed generation; Power (physics); Electrical engineering; Business; Economics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002587255,0.0001285699,0.0001490722,0.0001656104,0.00007522418,0.00006132169,0.0003805002,0.0000279061,0.00001123947],"category_scores_gemma":[0.00002074334,0.0001240169,0.00002264255,0.0004207287,0.0001240365,0.0003677278,0.0001493279,0.00004302175,0.000006756434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003738021,"about_ca_system_score_gemma":0.00002621404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001140868,"about_ca_topic_score_gemma":8.91199e-7,"domain_scores_codex":[0.9990298,0.000009401166,0.0001557782,0.0002728775,0.0002139652,0.0003182003],"domain_scores_gemma":[0.9994594,0.0001023666,0.00003374381,0.0001935717,0.0001100368,0.0001008289],"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":[0.0000185539,0.0001501524,0.00248993,0.0006319919,0.0001056505,0.000004261376,0.0009673027,0.7011121,0.05253784,0.003637343,0.05797089,0.180374],"study_design_scores_gemma":[0.0001734459,0.00003921787,0.02411325,0.00001325273,0.00000447642,0.000001884593,0.000001180661,0.9605568,0.01215202,0.000237471,0.002561825,0.000145194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2646866,0.0001359775,0.7334737,0.00006831194,0.0005013612,0.0002485758,0.000001693311,0.0001929811,0.0006908238],"genre_scores_gemma":[0.9803073,0.00001393187,0.01929712,0.0001142515,0.0001465164,0.00003871271,0.000001522475,0.00001470046,0.00006588308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7156208,"threshold_uncertainty_score":0.5057262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004359207612814838,"score_gpt":0.172118017588203,"score_spread":0.1677588099753882,"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."}}