{"id":"W2168464377","doi":"10.1051/e3sconf/20130134002","title":"Absence of mercury effects on fish populations of boreal reservoirs despite 3 to 6 fold increases in mercury concentrations","year":2013,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"WSP (Canada); Hydro-Québec","funders":"Hydro-Québec","keywords":"Esox; Coregonus clupeaformis; Pike; Salvelinus; Mercury (programming language); Catostomus; Fishery; Forage fish; Trout; Population; Biology; Fishing; Fish measurement; Environmental science; Ecology; Fish <Actinopterygii>","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001812186,0.0001266685,0.000302484,0.0001077531,0.00005131989,0.00001138916,0.0002132283,0.00004833661,0.0008660871],"category_scores_gemma":[0.0003698502,0.0001081664,0.00005244932,0.0004217963,0.0002728766,0.0002392768,0.00007802156,0.0000664887,0.00003068931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002603109,"about_ca_system_score_gemma":0.00009784605,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01190511,"about_ca_topic_score_gemma":0.003265533,"domain_scores_codex":[0.9987307,0.0001030156,0.0004425244,0.0001795646,0.0003554503,0.0001887558],"domain_scores_gemma":[0.9990546,0.0003667274,0.0002087079,0.0002072168,0.00006029571,0.0001024354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000197336,0.0001247851,0.9651157,0.00003879418,0.00001665685,5.824953e-7,0.0007439208,0.0002425868,0.02252892,0.004860648,0.003695592,0.002612095],"study_design_scores_gemma":[0.0002279165,0.000260394,0.9649314,0.0001683954,0.00001204937,3.063997e-7,0.0005251968,0.0001766476,0.0321057,0.001186791,0.0002964359,0.0001087176],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816656,0.00004315856,0.00002777807,0.0006133832,0.00006110358,0.0004242554,0.00004959485,0.00001009779,0.01710507],"genre_scores_gemma":[0.9991712,0.00006194817,0.0004836122,0.000134318,0.00001057121,0.00004850885,0.00001338112,0.000004839279,0.00007161278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01750565,"threshold_uncertainty_score":0.9946747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02879711620642313,"score_gpt":0.2832041444517979,"score_spread":0.2544070282453748,"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."}}