{"id":"W7133522051","doi":"10.1109/etfg61999.2025.11401213","title":"Geothermal-Based and Grid-Connected Energy Optimization of Smart Greenhouse Using Energy Valley Optimizer: A Case Study in Regina, Canada","year":2025,"lang":"","type":"article","venue":"","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Energy (signal processing); Greenhouse; Energy consumption; Renewable energy; Greenhouse gas; Efficient energy use","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003392841,0.0004625512,0.0008065003,0.000184774,0.0003880895,0.00005584072,0.000364105,0.0004259613,0.0003560377],"category_scores_gemma":[0.00008885446,0.0002568261,0.0000961,0.001376222,0.0002617834,0.0001409695,0.0002006519,0.0002091104,1.284181e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001818451,"about_ca_system_score_gemma":0.0003880753,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9516241,"about_ca_topic_score_gemma":0.9915392,"domain_scores_codex":[0.9971204,0.0004628366,0.0007825634,0.0007983153,0.0002280727,0.0006077715],"domain_scores_gemma":[0.9985816,0.0004641614,0.0003441587,0.0002597061,0.0002211517,0.0001291457],"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":[0.002426514,0.004575481,0.3180413,0.0001986539,0.0008915397,0.008206494,0.0002949284,0.6080439,0.006335421,0.004826064,0.001127942,0.0450317],"study_design_scores_gemma":[0.006192159,0.00156321,0.007956186,0.0002496631,0.0004095036,0.0002678283,0.008683482,0.971202,0.001661141,0.00008424126,0.0007556533,0.0009749147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935369,0.0009287735,0.001815433,0.002669363,0.0002495153,0.0004582162,0.00004212052,0.000098447,0.000201169],"genre_scores_gemma":[0.9981616,0.0002281322,0.0003539352,0.000733593,0.00003469288,0.00004145893,0.00001320821,0.000006298624,0.0004270623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3631581,"threshold_uncertainty_score":0.9999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321876295750136,"score_gpt":0.2129972695780823,"score_spread":0.1997785066205809,"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."}}