{"id":"W2798219492","doi":"10.1016/j.ecoenv.2018.04.004","title":"Mercury concentrations in blood, brain and muscle tissues of coastal and pelagic birds from northeastern Canada","year":2018,"lang":"en","type":"article","venue":"Ecotoxicology and Environmental Safety","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; Environment and Climate Change Canada; Acadia University","funders":"Natural Sciences and Engineering Research Council of Canada; Indigenous and Northern Affairs Canada; Acadia University","keywords":"Pelagic zone; Waterfowl; Mercury (programming language); Muscle tissue; Biology; Food chain; Predation; Zoology; Bioaccumulation; Ecology; Habitat; Anatomy","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":[0.00006102223,0.0002323651,0.0001690678,0.0005942927,0.001657845,0.0006048402,0.0002442205,0.0003017601,0.000932031],"category_scores_gemma":[0.0001638347,0.000179393,0.0001101586,0.000511835,0.0005697422,0.0001611845,0.0002073622,0.0002725477,0.0001973402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003189597,"about_ca_system_score_gemma":0.002337461,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8992993,"about_ca_topic_score_gemma":0.9503716,"domain_scores_codex":[0.9999156,0.000002895164,0.000003009168,0.00002605308,0.00002188606,0.00003053557],"domain_scores_gemma":[0.9998523,0.000008646693,0.00001678473,0.000003038188,0.00008078576,0.00003842631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002108381,0.0000948825,0.8576288,0.0001279449,0.000136397,0.0006989632,0.003730391,0.000392719,0.1156967,0.0001582326,0.00112997,0.01809662],"study_design_scores_gemma":[0.000004935994,0.0000690948,0.9943089,0.000005206989,0.00002822048,0.0001547545,0.001136581,0.00009754081,0.003402107,0.00001509816,0.0007719798,0.000005480252],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985946,0.0001776676,0.00005637814,0.00002617365,0.000002990649,0.000003915932,0.000380061,0.000004246299,0.0007539903],"genre_scores_gemma":[0.9939836,0.000289959,0.0001989771,0.00005544134,0.000002496311,0.000006097189,0.000493955,0.000004366142,0.004965199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1007007,"threshold_uncertainty_score":0.2025875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006588061440435018,"score_gpt":0.2109000450915637,"score_spread":0.2043119836511287,"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."}}