{"id":"W4287511339","doi":"10.1016/j.scitotenv.2022.157614","title":"Tracking the impacts of COVID-19 pandemic-related debris on wildlife using digital platforms","year":2022,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Dalhousie University","funders":"Environment and Climate Change Canada; Royal Society for the Prevention of Cruelty to Animals","keywords":"Wildlife; Context (archaeology); Pandemic; Sanitation; Personal protective equipment; Preparedness; Geography; Debris; Marine debris; Fishery; Microplastics; Environmental planning; Coronavirus disease 2019 (COVID-19); Environmental protection; Environmental health; Environmental resource management; Environmental science; Ecology; Medicine; Biology; Political science; Environmental engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001313843,0.0001324276,0.0001216964,0.00003152841,0.001137322,0.00002889934,0.0009860243,0.00002356897,0.0008537886],"category_scores_gemma":[0.0002179383,0.00006409921,0.0000970683,0.00039443,0.002114478,0.0001676322,0.001121792,0.0002383444,0.00002832747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007331151,"about_ca_system_score_gemma":0.00007720808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002698298,"about_ca_topic_score_gemma":0.000001952106,"domain_scores_codex":[0.997986,0.00004133443,0.0002956772,0.000245388,0.001105966,0.0003256945],"domain_scores_gemma":[0.9988723,0.0002018639,0.0003189642,0.0004952939,0.00000189884,0.0001097242],"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":[0.00003510595,0.00007275167,0.001620769,0.000002326076,0.000009539426,5.873493e-7,0.001223948,0.8878588,0.10827,0.0002300202,0.00008150989,0.0005946599],"study_design_scores_gemma":[0.003313285,0.001986942,0.311287,0.0001279036,0.0003832144,0.001278498,0.007701447,0.5728004,0.06968433,0.02592129,0.003904679,0.001610973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983307,0.00002264234,0.0001910991,0.0004112117,0.0001996467,0.0002719785,0.00006992123,0.000007154887,0.0004956652],"genre_scores_gemma":[0.999663,0.000009076351,0.0000283752,0.0001248715,0.000009289569,0.000004125618,0.000001067749,0.000007812417,0.0001523751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3150584,"threshold_uncertainty_score":0.9348387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209325092818156,"score_gpt":0.2305488795538284,"score_spread":0.2084556286256469,"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."}}