{"id":"W4318831516","doi":"10.1016/j.marpolbul.2023.114647","title":"Mercury bioaccumulation and speciation in coastal invertebrates: Implications for trophic magnification in a marine food web","year":2023,"lang":"en","type":"article","venue":"Marine Pollution Bulletin","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Acadia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Trophic level; Bioaccumulation; Biomagnification; Mercury (programming language); Methylmercury; Food web; Invertebrate; Environmental chemistry; Food chain; Ecology; Environmental science; Biology; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001555439,0.000144043,0.000152398,0.0005274292,0.0006501804,0.0005643895,0.0001835476,0.0002551278,0.001691099],"category_scores_gemma":[0.0004261528,0.0001482215,0.0001836526,0.0004392879,0.0003017057,0.0004611337,0.0005776451,0.0002131967,0.0001531137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005306602,"about_ca_system_score_gemma":0.0003042934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01353851,"about_ca_topic_score_gemma":0.03035097,"domain_scores_codex":[0.9999403,0.00001012402,0.00000451071,0.00001831787,0.00001663175,0.00001003566],"domain_scores_gemma":[0.9997978,0.00004293687,0.00004532024,0.00001270143,0.00005471223,0.00004664898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009145392,0.0001329469,0.6399049,0.0001252893,0.0001398251,0.0003011996,0.001551665,0.00060894,0.321281,0.0007710768,0.0002058507,0.03406263],"study_design_scores_gemma":[0.000005045084,0.0001403853,0.9938654,0.000005622403,0.00002900843,0.0001062562,0.000535018,0.0004314736,0.00437175,0.0001850403,0.0003195021,0.000005400499],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988176,0.00008714083,0.0001171808,0.00003216708,0.000001082299,0.000001349691,0.00003566913,0.000003464404,0.0009043607],"genre_scores_gemma":[0.9989132,0.0001359951,0.0003098624,0.00002130532,0.000002220325,0.000002361767,0.00005461213,0.000002422547,0.0005579842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01353851,"threshold_uncertainty_score":0.02691942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02961489090826969,"score_gpt":0.264327664847389,"score_spread":0.2347127739391193,"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."}}