{"id":"W4206062098","doi":"10.7901/2169-3358-2021.1.1141594","title":"A Simulation-based Contingency Planning Tool for Offshore Oil Spill Response","year":2021,"lang":"en","type":"article","venue":"International Oil Spill Conference Proceedings","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Memorial University of Newfoundland","funders":"","keywords":"Contingency plan; Submarine pipeline; Environmental science; Demand response; Resource (disambiguation); Emergency response; Engineering; Computer science; Electricity","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004775612,0.0002290375,0.0001910164,0.0001012642,0.0002191195,0.0002480991,0.0003057416,0.0001276704,0.002361867],"category_scores_gemma":[0.002457114,0.0002424886,0.0001355439,0.0002558227,0.0001100025,0.0003634574,0.0001054386,0.0001677632,0.000169706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002912626,"about_ca_system_score_gemma":0.0001001505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003044028,"about_ca_topic_score_gemma":0.00002169771,"domain_scores_codex":[0.9980846,0.000020828,0.0004333931,0.0005716615,0.0005738884,0.0003156145],"domain_scores_gemma":[0.9986545,0.0003455463,0.0002413749,0.0001146276,0.0005276425,0.0001162428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003767309,0.0004613599,0.2125227,0.0002505969,0.0001922134,0.00006016548,0.004736489,0.05781162,0.4209389,0.00796395,0.002807959,0.2884867],"study_design_scores_gemma":[0.003552809,0.0003288769,0.06678709,0.0004565979,0.00006790493,0.00002116856,0.0009692522,0.6525488,0.07309623,0.002657635,0.1983946,0.001119066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9638075,0.00002622319,0.006910661,0.002788211,0.0006527476,0.00009712853,0.00004374259,0.000159099,0.02551474],"genre_scores_gemma":[0.9884344,0.000008515932,0.003893794,0.001093717,0.0001577535,0.000128204,0.00005368867,0.00002770635,0.006202237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5947372,"threshold_uncertainty_score":0.9985501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02601688218782167,"score_gpt":0.2859988100454463,"score_spread":0.2599819278576246,"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."}}