{"id":"W4385283441","doi":"10.18280/ijdne.180314","title":"Evaluating and Optimizing Energy-Efficient Microclimate Control Systems in Vegetable Storage Facilities","year":2023,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Microclimate; Architectural engineering; Environmental science; Control (management); Process engineering; Engineering; Computer science; Automotive engineering; Geography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008163614,0.0001030649,0.000204795,0.0000993824,0.00007920744,0.00009160524,0.0001991898,0.0001820796,0.000007230167],"category_scores_gemma":[0.00008591689,0.00004922211,0.00004289461,0.0001377917,0.00004056916,0.0001124824,0.00004819285,0.000295354,0.000001425421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004189173,"about_ca_system_score_gemma":0.00001143896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003488993,"about_ca_topic_score_gemma":0.00006997948,"domain_scores_codex":[0.9990753,0.00008162607,0.0003145726,0.0001321891,0.0002159414,0.0001803529],"domain_scores_gemma":[0.9992235,0.0003539152,0.0001964859,0.0000231929,0.0001614068,0.00004152654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001277131,0.0002380051,0.01625509,0.00007102737,0.0005302212,0.0007062078,0.0009755854,0.294114,0.6013065,0.01092128,0.0003058125,0.07329915],"study_design_scores_gemma":[0.001694939,0.0004453818,0.0149586,0.0002350832,0.00004170594,0.0003960038,0.002073175,0.9766059,0.0003499743,0.001993884,0.000947788,0.00025756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944657,0.003342289,0.0007821013,0.0008412002,0.0003867212,0.00007572769,0.00004461886,0.00002960861,0.00003200636],"genre_scores_gemma":[0.9987171,0.0008345771,0.0002010314,0.00009466746,0.00008385188,0.000004420097,0.000008386636,0.000001365123,0.00005457872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.682492,"threshold_uncertainty_score":0.2007219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02108435801900553,"score_gpt":0.254764509453753,"score_spread":0.2336801514347474,"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."}}