{"id":"W4224017658","doi":"10.1130/g49942.1","title":"Relationship between glacial CO2 drawdown and mercury cycling in the western South Atlantic: An isotopic insight","year":2022,"lang":"en","type":"article","venue":"Geology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glacial period; Last Glacial Maximum; Geology; Interglacial; Oceanography; Biogeochemical cycle; Benthic zone; Holocene; North Atlantic Deep Water; Carbon cycle; Thermohaline circulation; Paleontology; Environmental chemistry; Chemistry; Ecology; Ecosystem","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003655856,0.00006989339,0.0001103065,0.00003595724,0.0003895033,0.00001238083,0.0001365915,0.00003352453,0.0003782089],"category_scores_gemma":[0.00005327048,0.00005454384,0.00001476021,0.0001428701,0.0001861739,0.00009443223,0.0002030344,0.0001977903,0.00005526084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002491443,"about_ca_system_score_gemma":0.000006363531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005129701,"about_ca_topic_score_gemma":0.0006879831,"domain_scores_codex":[0.9990937,0.0002852863,0.0001494262,0.0001641558,0.0001325995,0.0001748137],"domain_scores_gemma":[0.9995823,0.0002057277,0.00005033597,0.0001269506,0.00000184867,0.00003286878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004296226,0.00000979842,0.9829438,0.000001270868,0.000002239731,0.000004354601,0.01627018,0.00005584669,0.00002475165,0.0002163441,0.00009847142,0.0003686156],"study_design_scores_gemma":[0.0002050426,0.00006202409,0.9901209,6.184405e-7,0.000009645134,0.00001258013,0.001361509,0.0000197712,0.000004087131,0.001183144,0.006952838,0.00006786516],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959376,0.00004204735,0.00004458168,0.001639181,0.00007696175,0.0001347863,0.000003576903,0.00001287491,0.002108424],"genre_scores_gemma":[0.99888,0.000002975908,0.000030846,0.0007643915,0.00005679046,0.00002566041,0.00001857981,0.000003790038,0.0002169947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01490867,"threshold_uncertainty_score":0.4141123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03996670513400005,"score_gpt":0.2820266525910189,"score_spread":0.2420599474570189,"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."}}