{"id":"W2156786022","doi":"10.5430/air.v3n4p77","title":"A hybrid knowledge discovery system for oil spillage risks pattern classification","year":2014,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Adaptive neuro fuzzy inference system; Spillage; Computer science; Artificial neural network; Pruning; Artificial intelligence; Data mining; Pattern recognition (psychology); Machine learning; Identification (biology); Fuzzy logic; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002642729,0.0001269928,0.0001341237,0.0001220723,0.0005297184,0.0002152369,0.00032688,0.000075325,0.0002369145],"category_scores_gemma":[0.000453182,0.0001176905,0.00008827236,0.0003837004,0.0003233722,0.0003285726,0.0001346714,0.0002292721,0.004498669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004009068,"about_ca_system_score_gemma":0.0000244006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007832196,"about_ca_topic_score_gemma":0.0006740292,"domain_scores_codex":[0.9977859,0.0003272535,0.0003627125,0.0005047552,0.0005082565,0.0005111601],"domain_scores_gemma":[0.9989024,0.0004022278,0.0000718166,0.0003814985,0.00009204452,0.0001499509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003266104,0.00008985402,0.000541387,0.00005494226,0.000004190495,7.813804e-7,0.0002328788,0.0001342961,0.04404556,0.007132039,0.0004881627,0.9472433],"study_design_scores_gemma":[0.00008935076,0.0004130049,0.003449795,0.00009954459,0.00001277971,0.000009074726,0.002040221,0.2335073,0.7191127,0.01380317,0.02706818,0.0003949042],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6534648,0.0000278051,0.3145697,0.0005906516,0.0005963775,0.0004107504,0.00001557759,0.0001246327,0.03019967],"genre_scores_gemma":[0.9977141,0.00002645571,0.0001755939,0.00002719005,0.000285615,0.0002258235,0.00001528424,0.00002289135,0.001507031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9468483,"threshold_uncertainty_score":0.9962764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2054347238209183,"score_gpt":0.4084305841573663,"score_spread":0.202995860336448,"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."}}