{"id":"W2085527333","doi":"10.1109/isie.2006.295601","title":"Intelligent Fuzzy Control for Biogas in Hydrophobic Polymer System","year":2006,"lang":"en","type":"article","venue":"","topic":"Environmental and Analytical Chemistry Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fuzzy logic; Biogas; Fuzzy control system; Controller (irrigation); Control engineering; Computer science; MATLAB; Workspace; Block (permutation group theory); Adaptive neuro fuzzy inference system; Control theory (sociology); Engineering; Control (management); Artificial intelligence; Robot; Mathematics; Waste management","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006897723,0.0001120408,0.0001396293,0.0000115448,0.00005365909,0.000008916873,0.00009530572,0.00003670258,0.0004770349],"category_scores_gemma":[0.000002606681,0.00008544706,0.00006900707,0.00007766241,0.0001244594,0.00003719498,0.00006028878,0.0000370358,0.0003858378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001960745,"about_ca_system_score_gemma":0.000001020664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000860949,"about_ca_topic_score_gemma":0.0001456374,"domain_scores_codex":[0.9992009,0.000007779378,0.0001959903,0.0002319262,0.0001236432,0.0002397816],"domain_scores_gemma":[0.9997886,0.00003865755,0.00002652547,0.0001009393,8.521026e-7,0.00004437217],"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":[0.00009284674,0.0006207208,0.4275464,0.00007665884,0.00003993924,0.00002974849,0.00005593379,0.002446976,0.5503499,0.00925734,0.008316566,0.001166994],"study_design_scores_gemma":[0.003764977,0.0002466779,0.09709577,0.00007864154,0.0001019426,0.00002072082,0.001379926,0.00869842,0.8498381,0.002773467,0.03480102,0.001200335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8276622,0.0002542646,0.001320356,0.0006018621,0.00005667431,0.0003254898,0.00002403298,0.00005749808,0.1696977],"genre_scores_gemma":[0.9924774,0.000004684708,0.0001133192,0.0001352433,0.00003956046,0.00003873499,0.000005186964,0.000007189066,0.0071787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3304506,"threshold_uncertainty_score":0.5223198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00531249151181433,"score_gpt":0.1920423927675078,"score_spread":0.1867299012556934,"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."}}