{"id":"W3131381981","doi":"10.1016/j.jhazmat.2021.125405","title":"A Bayesian analysis of the factors determining microplastics ingestion in fishes","year":2021,"lang":"en","type":"article","venue":"Journal of Hazardous Materials","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":102,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada; Tula Foundation; University of Victoria","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada; University of Victoria","keywords":"Microplastics; Trophic level; Biomagnification; Ingestion; Biology; Ecology; Fishing; Fishery; Food chain; Aquatic environment; Environmental science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003393873,0.00008733261,0.0003175318,0.0001042356,0.00004123872,0.00003697484,0.0001399269,0.0000571427,0.0009604662],"category_scores_gemma":[0.000455289,0.00005886633,0.0001053128,0.0004354138,0.00005769863,0.00007261867,0.00008542847,0.00007780919,0.000002884318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009099478,"about_ca_system_score_gemma":0.00004197569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006586092,"about_ca_topic_score_gemma":0.0003986344,"domain_scores_codex":[0.9988648,0.0001318992,0.0005532169,0.00009093273,0.0002267196,0.0001324433],"domain_scores_gemma":[0.9991506,0.0001548739,0.0005137431,0.0001151144,0.00002594065,0.0000397583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003264005,0.00005070094,0.2066787,0.000009956396,0.0000896307,0.00003313262,0.0003738626,0.009823465,0.7825491,0.000005866461,0.0001062969,0.0002466648],"study_design_scores_gemma":[0.0001821704,0.00004071671,0.6329257,0.00007107997,0.0003272842,0.0000486795,0.00009782453,0.0005835984,0.3653722,0.00006473606,0.0002128124,0.00007315508],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975341,0.00001632918,0.001686508,0.00004767535,0.0005804094,0.00002773812,0.00004216533,0.000001513043,0.00006355011],"genre_scores_gemma":[0.9991676,0.00002015012,0.000732163,0.00001995604,0.00002529243,2.564718e-7,0.000002812686,0.0000055048,0.00002621828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.426247,"threshold_uncertainty_score":0.9999528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009051038152670325,"score_gpt":0.2107839481288037,"score_spread":0.2017329099761334,"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."}}