{"id":"W2065013185","doi":"10.1038/ngeo1134","title":"Methylation of inorganic mercury in polar marine waters","year":2011,"lang":"en","type":"article","venue":"Nature Geoscience","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":321,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Trent University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; ArcticNet","keywords":"Mercury (programming language); Environmental chemistry; Seawater; Water column; MERCURE; Methylmercury; Chemistry; Environmental science; Oceanography; Geology; Bioaccumulation","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003711189,0.00007783106,0.0001031738,0.00006576074,0.0000507668,0.000004352734,0.0002083349,0.00008195481,0.001093314],"category_scores_gemma":[0.0001198449,0.0000613771,0.00002260164,0.0005994584,0.0002188811,0.000288008,0.0001750616,0.0001560097,0.0000574623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004838483,"about_ca_system_score_gemma":0.000009716848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001086188,"about_ca_topic_score_gemma":0.0002926999,"domain_scores_codex":[0.9991617,0.00003222133,0.0001608312,0.0001871819,0.0002686722,0.0001893981],"domain_scores_gemma":[0.9997038,0.00002165933,0.00006924227,0.0001456343,0.00001052277,0.00004918874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000084518,0.00003937464,0.9462654,0.000004328985,0.000001946785,0.000001866259,0.002573533,0.000004798605,0.04636187,0.0003053212,0.0001775415,0.004255568],"study_design_scores_gemma":[0.0001041224,0.00003224235,0.978582,0.000004856007,0.000003589653,0.000002164324,0.0001550793,0.00004727464,0.01904828,0.001114248,0.0008248962,0.00008120977],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850661,0.00005517606,0.0001501779,0.0001170022,0.0001669725,0.00008993327,0.000003254105,0.00001260311,0.01433878],"genre_scores_gemma":[0.9979184,0.00003125129,0.001548071,0.0002034142,0.000007104469,0.000002392062,0.000001965798,0.000003435197,0.0002840236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03231664,"threshold_uncertainty_score":0.9998198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01355776867838615,"score_gpt":0.2422448817899031,"score_spread":0.2286871131115169,"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."}}