{"id":"W2922825360","doi":"10.1002/ieam.4147","title":"Estimating the Mass of Chemicals Associated with Ocean Plastic Pollution to Inform Mitigation Efforts","year":2019,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; University of Toronto","funders":"European Commission; American Chemistry Council","keywords":"Microplastics; Plastic pollution; Environmental science; Environmental chemistry; Pollution; Debris; Contamination; Seawater; Marine debris; Waste management; Environmental engineering; Oceanography; Chemistry; Geology; Ecology; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002295091,0.0001905649,0.0001584053,0.00004790945,0.0001222817,0.00003595202,0.000133866,0.00004922656,0.000671772],"category_scores_gemma":[0.00000993659,0.0001261581,0.00002967821,0.0002081521,0.0001252855,0.0001331282,0.0001526718,0.0001143335,0.00007868915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003872343,"about_ca_system_score_gemma":0.000005605038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003708401,"about_ca_topic_score_gemma":0.00001331856,"domain_scores_codex":[0.9987796,0.00002672188,0.0002749153,0.0002694183,0.0004063356,0.0002430384],"domain_scores_gemma":[0.9995186,0.00006910328,0.0001613931,0.0001669077,0.000003097855,0.00008089517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003057849,0.0006986323,0.4907169,0.0001636459,0.0006446354,0.00002080323,0.000901608,0.2490927,0.2228725,0.002879462,0.003547858,0.02815551],"study_design_scores_gemma":[0.001272685,0.0006066347,0.8826569,0.0002913626,0.0001821883,0.00000601591,0.0005806732,0.1061921,0.004766964,0.0003208435,0.002679886,0.0004438046],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798145,0.00000439299,0.01565952,0.0001339697,0.0001382049,0.0006642537,0.00003988723,0.00002110901,0.003524117],"genre_scores_gemma":[0.9949318,0.000009642844,0.004339883,0.000126577,0.000007578394,0.00001935071,0.0001016453,0.00001319733,0.0004502852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.39194,"threshold_uncertainty_score":0.7355432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003622253543905371,"score_gpt":0.2007215051206183,"score_spread":0.197099251576713,"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."}}