{"id":"W2214911374","doi":"10.2166/wpt.2015.109","title":"Pumps: energy efficiency & performance indicators","year":2015,"lang":"en","type":"article","venue":"Water Practice & Technology","topic":"Water Systems and Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"HydraTek (Canada)","funders":"","keywords":"Efficient energy use; Normalization (sociology); Work (physics); Context (archaeology); Energy consumption; Environmental economics; Energy conservation; Risk analysis (engineering); Engineering; Computer science; Business; Economics; Mechanical engineering; Electrical engineering; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002461583,0.0001423816,0.0001458982,0.0004427625,0.00005296758,0.0000363563,0.0002382213,0.0002405587,0.00001851027],"category_scores_gemma":[0.00006514857,0.0001086441,0.00001791582,0.0003877436,0.00005117785,0.0004648335,0.00007839284,0.0001940411,0.0004172098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008536703,"about_ca_system_score_gemma":0.00001548514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004519589,"about_ca_topic_score_gemma":0.00002398272,"domain_scores_codex":[0.999083,0.00002515334,0.0002273863,0.0001820244,0.0001452433,0.0003371214],"domain_scores_gemma":[0.9994526,0.00001238228,0.00004272076,0.000354131,0.00007139934,0.00006677763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001658522,0.0006453723,0.01316303,0.0003851221,0.0005203879,0.0001806864,0.01320661,0.8211181,0.01379221,0.01238205,0.0609162,0.06352442],"study_design_scores_gemma":[0.0002918327,0.00007779519,0.00001868981,0.00001185146,0.00002096916,0.0001551575,0.0001698921,0.01091057,0.05094715,0.0001094629,0.9370656,0.0002210404],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8056177,0.0008803763,0.1265752,0.002607922,0.002043922,0.0002510308,0.000002728511,0.003362438,0.05865869],"genre_scores_gemma":[0.9964991,0.00007379595,0.002113841,0.00006503813,0.00007117983,0.00004084028,0.0000146277,0.00003388975,0.001087642],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8761494,"threshold_uncertainty_score":0.5362527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042964739849706,"score_gpt":0.2091313570226332,"score_spread":0.1987017096241361,"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."}}