{"id":"W2044611148","doi":"10.5430/air.v2n4p13","title":"Experimental study of neuro-fuzzy-genetic framework for oil spillage risk management","year":2013,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Artificial Intelligence and Decision Support Systems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spillage; Adaptive neuro fuzzy inference system; Computer science; Analytics; MATLAB; Inference engine; Data mining; Software; Knowledge extraction; Artificial neural network; Inference; Fuzzy logic; Database; Machine learning; Artificial intelligence; Engineering; Operating system; Fuzzy control system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001678563,0.0003290382,0.0002951394,0.0004263828,0.0003437149,0.0005996281,0.0005983522,0.0005116306,0.001479937],"category_scores_gemma":[0.003780918,0.0001279902,0.000215679,0.0003515557,0.0004619105,0.0005774967,0.0004351754,0.0005711336,0.0001493591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005749837,"about_ca_system_score_gemma":0.0007757787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003099362,"about_ca_topic_score_gemma":0.002222306,"domain_scores_codex":[0.9993551,0.0002762681,0.00003466617,0.0000875288,0.0001983319,0.00004799134],"domain_scores_gemma":[0.9984384,0.0009564494,0.0001202171,0.0001511139,0.0002575847,0.00007623585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00377409,0.009611969,0.01273003,0.0006785168,0.0001810985,0.0005689016,0.001290751,0.6834993,0.105345,0.01612697,0.0008770952,0.1653163],"study_design_scores_gemma":[0.0001840802,0.005137337,0.004494362,0.0000264971,0.00004949163,0.00008948369,0.000466741,0.9363228,0.04850603,0.00319028,0.001492196,0.00004053428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609447,0.0001110273,0.03556172,0.0001234201,0.00002516613,0.0002117408,0.00007103408,0.0001225618,0.002828539],"genre_scores_gemma":[0.9811359,0.00006701901,0.01808293,0.00001612128,0.000003430456,0.0000837824,0.00004133523,0.000004539482,0.0005649493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003099362,"threshold_uncertainty_score":0.008877158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2117852498213675,"score_gpt":0.4454563822907867,"score_spread":0.2336711324694192,"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."}}