{"id":"W2134695704","doi":"10.1002/etc.2883","title":"Increase in mercury in Pacific yellowfin tuna","year":2015,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; National Science Foundation","keywords":"Mercury (programming language); Yellowfin tuna; Tuna; Environmental science; Fishery; Oceanography; Environmental chemistry; Biology; Fish <Actinopterygii>; Chemistry; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002115436,0.00013084,0.00015358,0.00001660452,0.00003626737,0.000005596714,0.00008079349,0.0001224301,0.001625276],"category_scores_gemma":[0.00003033511,0.0001316536,0.00001832298,0.00007377585,0.0004087935,0.0001037468,0.0001704326,0.0001735492,0.000164717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002297921,"about_ca_system_score_gemma":0.000007613448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000565282,"about_ca_topic_score_gemma":0.0000454274,"domain_scores_codex":[0.9991586,0.00004264908,0.000181988,0.0002574874,0.0001180521,0.0002412566],"domain_scores_gemma":[0.9996507,0.00003376308,0.000037927,0.0001180588,3.394515e-7,0.0001592292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004460297,0.0002238887,0.8228255,0.000005959966,0.000004746091,0.00005990101,0.001103759,0.00004332362,0.1713848,0.000003041053,0.002544519,0.001755969],"study_design_scores_gemma":[0.003254687,0.000115719,0.871297,0.00002243232,0.00001613777,0.0001154439,0.009037558,0.0001878276,0.0815511,0.001238068,0.03253695,0.000627093],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9585865,0.0002762412,0.000001217959,0.0002016255,0.00003253888,0.00007923225,0.000007214336,0.000009238433,0.0408062],"genre_scores_gemma":[0.9970186,0.0001537485,0.00005866767,0.0001757847,0.00001748611,0.00002450721,0.00001432071,0.000007114786,0.002529728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08983371,"threshold_uncertainty_score":0.9992874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205998047916199,"score_gpt":0.2284927807761952,"score_spread":0.2164328002970332,"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."}}