{"id":"W2551434836","doi":"10.1109/pesgm.2016.7741490","title":"Power consumption modeling of water pumping system for optimal energy management","year":2016,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Energy consumption; Schedule; Reliability (semiconductor); Rotational speed; Automotive engineering; Energy management; Power (physics); Computer science; Reliability engineering; Energy (signal processing); Control theory (sociology); Simulation; Engineering; Control (management); Electrical engineering; Mechanical 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":[0.0001277561,0.0001190071,0.000132326,0.0001182753,0.0000238905,0.00001114436,0.0001048072,0.0000367055,0.00009054893],"category_scores_gemma":[9.445534e-7,0.00007435231,0.00006007791,0.00002565524,0.000009246392,0.00009770536,0.00006006612,0.00001228024,0.00003252103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001042674,"about_ca_system_score_gemma":9.102939e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005488947,"about_ca_topic_score_gemma":0.000001583674,"domain_scores_codex":[0.9992298,0.000006686626,0.0002497392,0.0001504034,0.0001147105,0.0002486039],"domain_scores_gemma":[0.9996994,0.00001393586,0.00001330901,0.0002115504,0.00002840557,0.0000333829],"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":[0.00001290604,0.000006947512,0.00002099753,0.0003150742,0.0001510922,0.000001774429,0.00002051982,0.9578094,0.008006094,0.0323929,0.0003186023,0.0009436439],"study_design_scores_gemma":[0.0006210599,0.00001688464,0.00001272253,0.0001513121,0.00003080403,0.000001392204,0.00007073348,0.9029823,0.08952769,0.00004080844,0.00636556,0.0001787376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0772865,0.00002449759,0.9102055,0.00003044416,0.0004949126,0.0001177711,0.000003277399,0.0003166606,0.01152048],"genre_scores_gemma":[0.9936655,0.00003714877,0.005331315,0.00001168465,0.00004408477,0.00009469061,0.000004667752,0.00003411578,0.0007767898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.916379,"threshold_uncertainty_score":0.3031999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01177455257378479,"score_gpt":0.189880138039333,"score_spread":0.1781055854655482,"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."}}