{"id":"W4296162170","doi":"10.1016/j.watres.2022.119077","title":"Aggregation of microplastics and clay particles in the nearshore environment: Characteristics, influencing factors, and implications","year":2022,"lang":"en","type":"article","venue":"Water Research","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Fisheries and Oceans Canada; Environment and Climate Change Canada","keywords":"Microplastics; Sink (geography); Environmental science; Pollution; Salinity; Population; Oceanography; Environmental chemistry; Chemistry; Geology; Ecology; Biology; Geography","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":[0.0007355844,0.00005796778,0.00006746796,0.00004956138,0.0003128191,0.00003245655,0.0001206929,0.00002056123,0.0002649033],"category_scores_gemma":[0.00005069462,0.00003730135,0.000008460144,0.00009913899,0.00026497,0.00005079496,0.0003662902,0.000204257,0.00001294735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006711751,"about_ca_system_score_gemma":0.000005740044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003697309,"about_ca_topic_score_gemma":0.00003973749,"domain_scores_codex":[0.9990116,0.0001883125,0.0001534986,0.0001600522,0.00026208,0.0002244048],"domain_scores_gemma":[0.9996821,0.0001172159,0.0000266308,0.0001304745,0.000004562465,0.00003902594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001511123,0.00005034414,0.5472519,0.000009744802,0.000002887054,0.000002106957,0.004642603,0.0002269278,0.4452392,0.0001562739,0.00009527315,0.002307555],"study_design_scores_gemma":[0.0001544899,0.0001031948,0.9724906,0.000005636949,0.000005570521,0.00001253206,0.0007540804,0.001462851,0.02070431,0.0008844715,0.003349291,0.00007297742],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993008,0.00003076913,0.0001010611,0.0002840578,0.00001343503,0.0001551851,0.00005887164,0.000002307971,0.00005347947],"genre_scores_gemma":[0.9997805,0.00005287638,0.00007210307,0.00001905972,0.000007519587,0.0000204411,0.00002187185,0.00000498135,0.00002059789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4252386,"threshold_uncertainty_score":0.2900506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03441426711821717,"score_gpt":0.2664163040107099,"score_spread":0.2320020368924927,"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."}}