{"id":"W2112143468","doi":"10.1890/1051-0761(2001)011[0517:pmcifu]2.0.co;2","title":"PREDICTING MERCURY CONCENTRATION IN FISH USING MASS BALANCE MODELS","year":2001,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Bioenergetics; Mercury (programming language); Environmental science; Fish <Actinopterygii>; Energy balance; Ecology; Fishery; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003322522,0.0007407576,0.0003683601,0.0004260104,0.0002941809,0.0004157034,0.0006685762,0.0007388175,0.001154643],"category_scores_gemma":[0.0007829831,0.0002887311,0.0004412563,0.000302157,0.0002325136,0.0006821761,0.0002936079,0.0002709497,0.0002995187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069487,"about_ca_system_score_gemma":0.0006097078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02032341,"about_ca_topic_score_gemma":0.01921434,"domain_scores_codex":[0.9999219,0.00001856278,0.00000605747,0.0000230618,0.00002291942,0.000007464193],"domain_scores_gemma":[0.9998141,0.00009597728,0.00003270898,0.00001011753,0.00003963283,0.00000750037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006822219,0.00003169285,0.009005888,0.0000447965,0.00005048912,0.00003750627,0.00002490435,0.9632202,0.01210314,0.0007618553,0.0002386782,0.0144126],"study_design_scores_gemma":[0.00001541891,0.00004310113,0.002126633,0.000002953965,0.00001573361,0.00001048994,0.000006935984,0.9932618,0.003115754,0.0009642343,0.0004292218,0.000007810751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6630582,0.0002665254,0.3294607,0.0002449419,0.000041596,0.0001172282,0.0008113714,0.001154637,0.004844784],"genre_scores_gemma":[0.9549927,0.0001914328,0.04174176,0.00003653053,0.00001088309,0.0001681695,0.0003264393,0.00004794417,0.002484068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02032341,"threshold_uncertainty_score":0.04041028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03958738108036285,"score_gpt":0.2817819361475964,"score_spread":0.2421945550672335,"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."}}