{"id":"W2141913840","doi":"10.1016/j.envpol.2014.11.007","title":"Spatio-temporal variations in biomass and mercury concentrations of epiphytic biofilms and their host in a large river wetland (Lake St. Pierre, Qc, Canada)","year":2014,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Università degli Studi di Camerino; Parks Canada","keywords":"Epiphyte; Macrophyte; Methylmercury; Wetland; Environmental chemistry; Mercury (programming language); Environmental science; Ecology; Autotroph; Aquatic plant; Periphyton; Bioaccumulation; Algae; Chemistry; Biology","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":[0.000137291,0.000197328,0.0003052412,0.0006226469,0.001726388,0.0008031483,0.0005784263,0.0003725251,0.0007967887],"category_scores_gemma":[0.0002168602,0.000249355,0.0002185892,0.0007229822,0.0006814337,0.0002297721,0.0005821205,0.0003313282,0.0001428096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006402884,"about_ca_system_score_gemma":0.003815373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9246934,"about_ca_topic_score_gemma":0.9722802,"domain_scores_codex":[0.9998295,0.00000797644,0.000003952399,0.0000449985,0.00003656468,0.00007693385],"domain_scores_gemma":[0.9997095,0.00002622978,0.00004092654,0.000006762227,0.0001308566,0.00008564891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005726074,0.0001453761,0.9325017,0.00007205064,0.000121432,0.000476276,0.00361916,0.0008030107,0.05274117,0.0001897425,0.001037548,0.007719957],"study_design_scores_gemma":[0.00000183269,0.00001254541,0.9987142,0.000002303537,0.000007061303,0.00001577774,0.000685008,0.0002425872,0.0002029159,0.000005581967,0.000106302,0.000003815326],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991993,0.00004038939,0.0000415633,0.00001888472,9.757363e-7,0.000005382228,0.0003015548,0.000003748203,0.0003881868],"genre_scores_gemma":[0.9988095,0.00003966508,0.0001306839,0.00001425541,9.682674e-7,0.00000853631,0.0002225708,0.000001686107,0.0007721435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07530659,"threshold_uncertainty_score":0.1515001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00629612616736847,"score_gpt":0.1980780563866217,"score_spread":0.1917819302192532,"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."}}