{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007706882,0.001096955,0.0005723172,0.0007702782,0.0004618002,0.0009120513,0.00129648,0.0007719241,0.02723564],"category_scores_gemma":[0.001502635,0.0005788774,0.0007696758,0.0004191749,0.0002808253,0.0006995401,0.0009153016,0.0009833711,0.00319889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004894448,"about_ca_system_score_gemma":0.0009412016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004455874,"about_ca_topic_score_gemma":0.004500073,"domain_scores_codex":[0.9997436,0.00007295873,0.00002597116,0.00004447306,0.00008698024,0.00002598342],"domain_scores_gemma":[0.9993622,0.0003958274,0.00003982872,0.00005088883,0.0001011161,0.00005022276],"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":[0.0004394502,0.0002615545,0.002344543,0.0003772847,0.0001097363,0.0005282329,0.0003367615,0.7738391,0.01060608,0.01475418,0.0382726,0.1581306],"study_design_scores_gemma":[0.00009603787,0.0000323054,0.0002504573,0.00003568166,0.00001633995,0.000047061,0.0000313141,0.9721166,0.003026925,0.003331023,0.02099288,0.0000234681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01093083,0.0001081631,0.9218303,0.0001901387,0.0000748474,0.0003221888,0.002206263,0.0529158,0.01142145],"genre_scores_gemma":[0.2479501,0.0004135413,0.7251647,0.0002146365,0.00004859827,0.001486748,0.006127236,0.004702501,0.013892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02723564,"threshold_uncertainty_score":0.09111226,"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."}}