{"id":"W4382393601","doi":"10.3389/fmars.2023.1232888","title":"Editorial: Cleaning litter by developing and applying innovative methods in European seas","year":2023,"lang":"en","type":"editorial","venue":"Frontiers in Marine Science","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Horizon 2020 Framework Programme","keywords":"Marine debris; Environmental science; Oceanography; Litter; Volume (thermodynamics); Pollution; Environmental planning; Environmental protection; Environmental resource management; Engineering; Waste management; Geology; Ecology; Biology","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":[0.005474301,0.005050218,0.003235737,0.003222812,0.002694519,0.005441868,0.002885981,0.01269221,0.0226782],"category_scores_gemma":[0.01409128,0.000904573,0.002814826,0.001119865,0.001649014,0.003784799,0.001453777,0.01174407,0.01907121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002027068,"about_ca_system_score_gemma":0.002108352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001078858,"about_ca_topic_score_gemma":0.003334429,"domain_scores_codex":[0.9967783,0.000449228,0.0004236899,0.0004530777,0.001653063,0.0002426197],"domain_scores_gemma":[0.9895025,0.002822587,0.0007403669,0.0002730017,0.004782653,0.001878802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005317953,0.00001332565,0.0000196635,0.0001592123,0.00001328568,0.00008071167,0.000005955357,0.00002134966,0.00008193588,0.000124109,0.9952183,0.004208942],"study_design_scores_gemma":[0.00008180678,0.00004078706,0.000286977,0.000330736,0.00004691751,0.0002115511,0.00002931043,0.0001291372,0.0002042035,0.0007498348,0.9978714,0.00001735898],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00003411865,0.002693426,0.0001042115,0.01734152,0.9782894,0.00002114823,0.00006590794,0.00005569692,0.001394433],"genre_scores_gemma":[0.0004635942,0.003427475,0.0001234718,0.0170704,0.9662288,0.00002542908,0.00005687428,0.00004433989,0.01255958],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0226782,"threshold_uncertainty_score":0.0758661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008405946645175633,"score_gpt":0.272232511840771,"score_spread":0.2638265651955953,"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."}}