{"id":"W3138609085","doi":"10.18280/i2m.200105","title":"Greenhouse Climate Controller by Using of Internet of Things Technology and Fuzzy Logic","year":2021,"lang":"en","type":"article","venue":"Instrumentation Mesure Métrologie","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Direction Générale de la Recherche Scientifique et du Développement Technologique","keywords":"Fuzzy logic; Greenhouse; Computer science; Wireless sensor network; Controller (irrigation); Arduino; Embedded system; Real-time computing; The Internet; Computer network; Operating system; 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":[0.0002718862,0.0001480871,0.0003814953,0.00005261617,0.00007012796,0.00001419543,0.0001930731,0.0003023063,0.0001046646],"category_scores_gemma":[0.0001156296,0.00007152804,0.00007048173,0.0003981304,0.0002951719,0.0001515381,0.0001421075,0.0001575635,0.00000290296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001599657,"about_ca_system_score_gemma":0.000009967714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006832839,"about_ca_topic_score_gemma":0.00005021238,"domain_scores_codex":[0.9988002,0.0001013189,0.0004221266,0.0002871842,0.000131847,0.0002572773],"domain_scores_gemma":[0.9993048,0.0001259501,0.0003227666,0.00007367416,0.000140744,0.0000320206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001054364,0.00008438587,0.1387305,0.00002009583,0.00005722023,0.000006011673,0.00004804993,0.000002040602,0.8090717,0.00412613,0.00005289614,0.04769548],"study_design_scores_gemma":[0.005903463,0.002294939,0.1266598,0.0001493868,0.0003380671,0.0001928967,0.00417522,0.001704441,0.8114334,0.04544798,0.0009353553,0.0007650354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965277,0.0008565382,0.00007627689,0.001964497,0.00006091427,0.0001633584,0.0000543426,0.0001178366,0.0001784951],"genre_scores_gemma":[0.9985067,0.0002645711,0.0008198869,0.0003347207,0.000009341517,0.00001031119,0.00003266647,0.00000170715,0.000020114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04693044,"threshold_uncertainty_score":0.2916829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02037668741178029,"score_gpt":0.2509291189118822,"score_spread":0.230552431500102,"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."}}