{"id":"W4393253541","doi":"10.3390/smartcities7020036","title":"Optimizing Energy Consumption in Agricultural Greenhouses: A Smart Energy Management Approach","year":2024,"lang":"en","type":"article","venue":"Smart Cities","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Mitacs; Petroleum Technology Research Centre","keywords":"Greenhouse; Energy consumption; Agriculture; Agricultural engineering; Consumption (sociology); Environmental science; Energy management; Energy (signal processing); Environmental economics; Business; Agricultural economics; Natural resource economics; Economics; Engineering; Geography; Agronomy; Mathematics; Electrical engineering; Art","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003957132,0.0006384568,0.0004915239,0.0003496341,0.0002420978,0.0007443886,0.0004168905,0.0004754626,0.0009881608],"category_scores_gemma":[0.0003889528,0.0002385019,0.0004305569,0.0004258947,0.0003423716,0.000935868,0.0005292711,0.0004144625,0.0001436179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000483515,"about_ca_system_score_gemma":0.000586936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001670416,"about_ca_topic_score_gemma":0.003129857,"domain_scores_codex":[0.999863,0.00004042528,0.00000555558,0.00003562894,0.00003827115,0.00001702683],"domain_scores_gemma":[0.9999038,0.00004509266,0.0000166366,0.000009826226,0.000018426,0.00000607963],"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":[0.00003965551,0.00004771189,0.001081051,0.0001227483,0.000040321,0.00006223267,0.0000418886,0.9382071,0.0106137,0.007120933,0.0006536249,0.04196905],"study_design_scores_gemma":[0.000008958538,0.00006930361,0.000835954,0.00001244103,0.00002298132,0.0000241089,0.00006197164,0.9863982,0.003343191,0.006450899,0.002759772,0.00001227154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08096846,0.001223621,0.904406,0.0005452014,0.00005348527,0.00007653474,0.0001199839,0.0003006988,0.01230604],"genre_scores_gemma":[0.9190213,0.0008989868,0.07638407,0.0001066758,0.0000326884,0.0000825915,0.0001109097,0.00007520429,0.003287514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001670416,"threshold_uncertainty_score":0.003508151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01725213772227157,"score_gpt":0.1999108679059316,"score_spread":0.18265873018366,"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."}}