{"id":"W4280558511","doi":"10.21203/rs.3.rs-1668158/v1","title":"Fate of microplastics in background headwater lake catchments using a particle balance approach","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de l’Environnement, de la Protection de la nature et des Parcs; Trent University; University of Windsor","keywords":"Microplastics; Environmental science; Deposition (geology); Flux (metallurgy); Plastic pollution; Sink (geography); Hydrology (agriculture); Pollution; Environmental chemistry; Ecology; Structural basin; Geology; Geography; Chemistry; Biology; Geomorphology","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":[0.0002231441,0.0003407917,0.000329325,0.0008298806,0.0006328506,0.0008522882,0.000287552,0.0002643424,0.0007793408],"category_scores_gemma":[0.0002117038,0.0001955046,0.0002833453,0.0006618847,0.0002092565,0.0003527444,0.0002936459,0.00015124,0.0001282485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003234758,"about_ca_system_score_gemma":0.001255616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4173498,"about_ca_topic_score_gemma":0.5050673,"domain_scores_codex":[0.9998938,0.000007723185,0.00000617237,0.00003372615,0.00004094474,0.00001753806],"domain_scores_gemma":[0.9999013,0.00001453283,0.00002222249,0.000004240218,0.00004619888,0.00001145668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007647786,0.000186852,0.7603872,0.0002557678,0.0002290414,0.000228002,0.000910043,0.01604033,0.1980015,0.0002132835,0.0003964005,0.02238672],"study_design_scores_gemma":[0.00003022308,0.0001631134,0.9507927,0.000009968397,0.00006317777,0.00003003723,0.0003070949,0.0326347,0.01506038,0.00007118003,0.0008210457,0.0000164305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998462,0.00006961777,0.0005757615,0.000008193318,9.154102e-7,0.00002887276,0.0004626074,0.00001173911,0.0003802339],"genre_scores_gemma":[0.9964992,0.0001326608,0.00171904,0.00001190098,0.00000189414,0.00003637584,0.000671527,0.000007991421,0.0009194768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4173498,"threshold_uncertainty_score":0.8298411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08727886288860318,"score_gpt":0.3559218234342145,"score_spread":0.2686429605456113,"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."}}