{"id":"W4404485244","doi":"10.1039/d4en00954a","title":"Nanotechnology for oil spill response and cleanup in coastal regions","year":2024,"lang":"en","type":"article","venue":"Environmental Science Nano","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Fisheries and Oceans Canada; Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Oil spill; Environmental science; Environmental chemistry; Petroleum engineering; Environmental engineering; Geology; Chemistry","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":[0.0003997175,0.0002056394,0.0001709883,0.0005242247,0.0005476372,0.0009440859,0.000206487,0.0007548871,0.002751705],"category_scores_gemma":[0.0006261814,0.00009850275,0.0001891048,0.0002991046,0.0004063348,0.000642425,0.0006771574,0.0003708144,0.000585562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009502586,"about_ca_system_score_gemma":0.001394231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003533631,"about_ca_topic_score_gemma":0.009800923,"domain_scores_codex":[0.9998376,0.00004378051,0.000008991348,0.00002310941,0.00005174094,0.00003472074],"domain_scores_gemma":[0.9997321,0.00005522982,0.00006242949,0.00001585524,0.00009684375,0.00003746564],"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":[0.0004816507,0.0003411545,0.01635989,0.001864393,0.00009911888,0.0005230359,0.0003196263,0.008647149,0.426355,0.01615737,0.01464228,0.5142093],"study_design_scores_gemma":[0.00008204057,0.002161834,0.04044283,0.001324396,0.0002180562,0.001363873,0.004204593,0.01549799,0.5261856,0.02521688,0.3831871,0.0001148263],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6815507,0.1389288,0.02518151,0.03169936,0.0009922694,0.0001700133,0.0005515006,0.0004565969,0.1204692],"genre_scores_gemma":[0.9101012,0.06013602,0.01408015,0.001323002,0.0001387626,0.00006125163,0.0001099957,0.00003561968,0.01401406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003533631,"threshold_uncertainty_score":0.009205401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006557428790781489,"score_gpt":0.2236953201878944,"score_spread":0.2171378913971129,"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."}}