{"id":"W2575654528","doi":"10.1007/s00244-017-0364-2","title":"Thyroid Hormones, Retinol and Clinical Parameters in Relation to Mercury and Organohalogen Contaminants in Great Blue Heron (Ardea herodias) Nestlings from the St. Lawrence River, Québec, Canada","year":2017,"lang":"en","type":"article","venue":"Archives of Environmental Contamination and Toxicology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal; Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Ardea; Heron; Estuary; Feather; Ecotoxicology; Mercury (programming language); Biology; Environmental chemistry; Zoology; Population; Triiodothyronine; Ecology; Hormone; Endocrinology; Chemistry; Medicine","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":[0.000194063,0.000262824,0.0002574101,0.0006774786,0.001271601,0.0005573712,0.0005296771,0.0003782985,0.001091836],"category_scores_gemma":[0.0004274947,0.0002236549,0.0001774055,0.0008139135,0.0006976221,0.0001661669,0.00021854,0.0005621513,0.00023105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006661762,"about_ca_system_score_gemma":0.003462122,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8988814,"about_ca_topic_score_gemma":0.9603932,"domain_scores_codex":[0.9998156,0.00001810745,0.000007983269,0.00003845163,0.00005265744,0.00006713423],"domain_scores_gemma":[0.9993238,0.00004885452,0.00009449918,0.00001948391,0.0002978525,0.0002155396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002900645,0.0001123048,0.9928444,0.00001467644,0.00004566658,0.0003382381,0.0006845158,0.0001026548,0.002962527,0.00002617661,0.0004991054,0.002079595],"study_design_scores_gemma":[0.000002127451,0.00004794155,0.999024,0.000002876578,0.000006732297,0.00006327802,0.0005281284,0.00003584809,0.0000950162,0.000004027398,0.00018696,0.000002985451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986307,0.0002357321,0.00002292045,0.0000405551,0.000004014357,0.00000833383,0.0004515168,0.000003291751,0.0006029978],"genre_scores_gemma":[0.9970925,0.000137988,0.00006046569,0.00004648692,0.000002439171,0.000008996674,0.0004510549,0.000002502746,0.002197522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1011186,"threshold_uncertainty_score":0.2034282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01566044148150803,"score_gpt":0.2505620798810246,"score_spread":0.2349016383995166,"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."}}