{"id":"W2985478087","doi":"10.1016/j.marpolbul.2019.110722","title":"Benthic marine debris in the Bay of Fundy, eastern Canada: Spatial distribution and categorization using seafloor video footage","year":2019,"lang":"en","type":"article","venue":"Marine Pollution Bulletin","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Bedford Institute of Oceanography; Dalhousie University; Nova Scotia Community College","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Marine debris; Benthic zone; Debris; Plastic pollution; Bay; Environmental science; Oceanography; Fishing; Seafloor spreading; Marine spatial planning; Marine pollution; Commercial fishing; Fishery; Marine protected area; Microplastics; Geology; Pollution; Habitat; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002681956,0.0002699217,0.0002056075,0.002246685,0.00145104,0.001224788,0.0004637543,0.0002179185,0.001104385],"category_scores_gemma":[0.0007698954,0.0001922664,0.0001735532,0.003484638,0.0006862146,0.0002566609,0.0008299957,0.0002041225,0.0002105008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007975576,"about_ca_system_score_gemma":0.007110682,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9846292,"about_ca_topic_score_gemma":0.9949228,"domain_scores_codex":[0.9997101,0.00001382936,0.00001632312,0.0000515074,0.000123002,0.00008515735],"domain_scores_gemma":[0.9991431,0.00005465743,0.0001519532,0.00001733213,0.0004710141,0.0001618444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006035763,0.00001488877,0.9830143,0.00005587036,0.00002276308,0.0001820237,0.00265317,0.00008281969,0.001484434,0.00002958408,0.0003869745,0.01201272],"study_design_scores_gemma":[9.079718e-7,0.00001035179,0.996905,0.00001393144,0.000003859798,0.00002798867,0.00246276,0.0000599012,0.00005811518,0.000003707085,0.0004503001,0.00000322047],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965969,0.0002724969,0.0001068494,0.00003552492,0.00000226198,0.00003244801,0.001570584,0.000006921507,0.001376062],"genre_scores_gemma":[0.9954363,0.0004405969,0.0005394327,0.00003581701,0.00000196143,0.00002396682,0.00129197,0.00000328308,0.002226796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01537085,"threshold_uncertainty_score":0.05786717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005689005681467265,"score_gpt":0.1778527579001666,"score_spread":0.1721637522186993,"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."}}