{"id":"W3001137674","doi":"10.1007/s10933-020-00111-7","title":"Effects of climate variability on mercury deposition during the Older Dryas and Younger Dryas in the Venezuelan Andes","year":2020,"lang":"en","type":"article","venue":"Journal of Paleolimnology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Younger Dryas; Deglaciation; Holocene; Climate change; Abrupt climate change; Geology; Glacial period; Physical geography; Mercury (programming language); Allerød oscillation; Last Glacial Maximum; Sediment; Ice core; Oceanography; Climatology; Global warming; Geomorphology; Effects of global warming; Geography","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":[0.00048875,0.00007866407,0.0001772865,0.0000238603,0.00008814316,0.000009271218,0.0001287515,0.00004630474,0.00005540331],"category_scores_gemma":[0.0001783314,0.00004173183,0.00004456729,0.0001136537,0.0002117807,0.0001034091,0.00005578802,0.0002059937,0.000005642236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002333291,"about_ca_system_score_gemma":0.000005004418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001128906,"about_ca_topic_score_gemma":0.00001728422,"domain_scores_codex":[0.9990158,0.0003247885,0.0002598662,0.00009010001,0.0001664094,0.0001430233],"domain_scores_gemma":[0.9992871,0.0003863167,0.0001983939,0.00007928647,0.00001004359,0.00003886496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002256469,0.0001273482,0.8924001,0.0001330588,0.00005362091,0.00005448347,0.01367457,0.0001321753,0.08953518,0.0001730592,0.00009635984,0.003394325],"study_design_scores_gemma":[0.0005142864,0.0002350491,0.9922796,0.00002912624,0.00003500839,0.00006161289,0.0005142576,0.00002549004,0.005990582,0.0002162969,0.0000553673,0.00004333353],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958428,0.0002517563,0.00003573814,0.003046331,0.00007451002,0.0001316283,0.000001370109,0.000002639898,0.0006132516],"genre_scores_gemma":[0.9987236,0.00056033,0.00004410209,0.0006106287,0.00005279515,0.000003267316,2.03296e-7,0.000003201937,0.00000193185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09987942,"threshold_uncertainty_score":0.1701775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007323726217230023,"score_gpt":0.2381003719489006,"score_spread":0.2307766457316706,"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."}}