{"id":"W2081911395","doi":"10.1109/tsg.2014.2325553","title":"Optimal Operation of Climate Control Systems of Produce Storage Facilities in Smart Grids","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Energy storage; Smart grid; Context (archaeology); Electricity; Computer science; Demand response; Reliability engineering; Monte Carlo method; Optimal control; Control (management); Mathematical optimization; Engineering; Power (physics); Electrical 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":[0.0004091671,0.0006170215,0.0007295409,0.0002583757,0.0004258424,0.001025491,0.0005396818,0.0007873211,0.002036947],"category_scores_gemma":[0.0008850937,0.0003829169,0.0006399149,0.0002840485,0.0006629119,0.001096241,0.0005101825,0.0006607103,0.000202798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036837,"about_ca_system_score_gemma":0.001045904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006476004,"about_ca_topic_score_gemma":0.005498237,"domain_scores_codex":[0.9997782,0.00006764063,0.000007683565,0.00004624441,0.00006048401,0.00003983295],"domain_scores_gemma":[0.9997539,0.0001201954,0.00006524831,0.0000123246,0.00003672939,0.00001167555],"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":[0.00001200851,0.000005545955,0.00009835655,0.000009812153,0.000004115815,0.00001146114,0.00001025291,0.9940802,0.0003673953,0.00435174,0.00008749015,0.0009615467],"study_design_scores_gemma":[0.000004383483,0.00000895007,0.00005888553,0.000001600667,0.000002411832,0.000002732503,0.000005031553,0.9984093,0.0001751982,0.001185248,0.0001440896,0.000002035333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08016318,0.0003994366,0.903587,0.0004317937,0.00004680608,0.00006663902,0.0002188348,0.0002037049,0.01488257],"genre_scores_gemma":[0.9838287,0.0002820796,0.01222318,0.00003694772,0.00001266131,0.00008910573,0.00006077711,0.00002619831,0.003440479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006476004,"threshold_uncertainty_score":0.01287663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006821850918684254,"score_gpt":0.188048236745773,"score_spread":0.1812263858270888,"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."}}