{"id":"W3212017712","doi":"10.3389/fmars.2021.618094","title":"A Fuzzy-Based Framework for Assessing Uncertainty in Drift Prediction Using Observed Currents and Winds","year":2021,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; York University; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; National Oceanic and Atmospheric Administration; Government of Canada","keywords":"Drifter; Trajectory; Meteorology; Forcing (mathematics); Ocean current; Environmental science; Focus (optics); Drag; Current (fluid); Computer science; Geology; Mechanics; Mathematics; Physics; Climatology; Lagrangian; Applied mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003617876,0.001409731,0.001045587,0.001864001,0.0007334761,0.001968991,0.002388228,0.001337883,0.001236028],"category_scores_gemma":[0.006397728,0.0005094096,0.001377666,0.001060884,0.001579535,0.002356966,0.001085564,0.001267747,0.0001731659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002098674,"about_ca_system_score_gemma":0.001671685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01718504,"about_ca_topic_score_gemma":0.00832044,"domain_scores_codex":[0.9987119,0.0004275464,0.0001014762,0.0003064974,0.0003652038,0.00008735126],"domain_scores_gemma":[0.9973375,0.001569577,0.0004058236,0.0001421393,0.0004442261,0.0001007818],"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":[0.00001231392,0.00001030339,0.0003722077,0.00001923667,0.00002312684,0.00003323491,0.00002816957,0.9788961,0.000342283,0.01395458,0.00009979754,0.006208694],"study_design_scores_gemma":[0.000002499939,0.00001551814,0.00009855258,0.000008557176,0.000005263965,0.000007818252,0.00000777905,0.9915624,0.0001154237,0.008007697,0.0001605886,0.000007977998],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006405902,0.00008504663,0.9925074,0.00006976337,0.00001849374,0.00001838599,0.0000639674,0.00005741326,0.0007736059],"genre_scores_gemma":[0.6494139,0.0003275068,0.3483575,0.00007228613,0.00009842178,0.000211149,0.0002239525,0.00003735193,0.001257838],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01718504,"threshold_uncertainty_score":0.03417003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02583529886522618,"score_gpt":0.2581306884986567,"score_spread":0.2322953896334305,"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."}}