{"id":"W3014090388","doi":"10.1680/jenes.19.00054","title":"Research on intelligent control of an agricultural greenhouse based on fuzzy PID control","year":2020,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse; Agriculture; PID controller; Agricultural engineering; Intelligent control; Temperature control; Control (management); Computer science; Environmental science; Control engineering; Engineering; Agronomy; Ecology; 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":[0.0007726098,0.0001147194,0.000215653,0.00005395266,0.0001419206,0.00002888495,0.0003828769,0.00006458395,0.00004110836],"category_scores_gemma":[0.000101645,0.000045708,0.00006531021,0.0002627172,0.0002998209,0.0001464658,0.00002755097,0.0003529114,0.000005998492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004210382,"about_ca_system_score_gemma":0.000007742012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003320223,"about_ca_topic_score_gemma":0.00000140609,"domain_scores_codex":[0.9986942,0.00004976858,0.0002603602,0.0001970568,0.0005386663,0.0002599802],"domain_scores_gemma":[0.999342,0.0002301007,0.0001124377,0.00005307315,0.00002911446,0.0002333264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002103449,0.0001657471,0.001289076,0.000004635803,0.000009008242,0.00001574215,0.00004803648,0.01668486,0.9722858,0.0001704472,0.00001040591,0.009105898],"study_design_scores_gemma":[0.002659959,0.01783357,0.7889201,0.0001385052,0.0000466114,0.00006673377,0.001633904,0.09515855,0.09225523,0.00005676728,0.0008050768,0.0004250127],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981667,0.00008808265,0.00007388499,0.001415154,0.00004951822,0.0001062824,0.00002267167,0.0000180035,0.00005971824],"genre_scores_gemma":[0.9995561,0.00002893332,0.0000524347,0.000270881,0.00008483585,0.000002019352,6.241163e-7,0.000001238924,0.000002894635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8800306,"threshold_uncertainty_score":0.1863918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02068868879387776,"score_gpt":0.2255099083258033,"score_spread":0.2048212195319255,"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."}}