{"id":"W2734399764","doi":"","title":"A fuzzy inference system for diagnosing oil palm nutritional deficiency symptoms","year":2017,"lang":"en","type":"article","venue":"ARPN Journal of Engineering and Applied Sciences","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Palm oil; Fuzzy inference system; Fuzzy inference; Inference system; Computer science; Inference; Palm; Fuzzy logic; Artificial intelligence; Machine learning; Adaptive neuro fuzzy inference system; Fuzzy control system; Food science; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007652616,0.0005755907,0.0009667202,0.0007959677,0.0009543233,0.0009023598,0.000932556,0.001274669,0.003008898],"category_scores_gemma":[0.001064167,0.0003668271,0.0005638005,0.000397368,0.0002077337,0.000475867,0.0004267214,0.0006307623,0.0009003502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006283185,"about_ca_system_score_gemma":0.00100539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009515715,"about_ca_topic_score_gemma":0.0113746,"domain_scores_codex":[0.9996281,0.00004609192,0.00004878422,0.000120454,0.0001090861,0.00004756501],"domain_scores_gemma":[0.9994758,0.0001579383,0.00003436963,0.00003593808,0.0002604446,0.000035609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002094321,0.0007682426,0.01177961,0.0008178758,0.0003909796,0.001486429,0.0004743711,0.05652536,0.1901003,0.002091611,0.00752659,0.7259443],"study_design_scores_gemma":[0.0003027473,0.0009413087,0.01322258,0.0001216362,0.0007193983,0.0008670035,0.0001990062,0.9332967,0.04276981,0.001796243,0.005643556,0.0001200564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1699459,0.001458842,0.8135496,0.0003977396,0.0005123439,0.000519356,0.0006442015,0.004990217,0.007981922],"genre_scores_gemma":[0.8432153,0.0003122148,0.1507171,0.0002231339,0.00009322901,0.0002620664,0.0003720857,0.0000308849,0.004774076],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009515715,"threshold_uncertainty_score":0.01892066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669801278106612,"score_gpt":0.2311200200049801,"score_spread":0.214422007223914,"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."}}