{"id":"W4240737601","doi":"10.5194/bg-2021-39","title":"Sediment and carbon accumulation in a glacial lake in Chukotka (ArcticSiberia) during the late Pleistocene and Holocene: Combining hydroacoustic profiling and down-core analyses","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; Ministry of Science and Higher Education of the Russian Federation; Bundesministerium für Bildung und Forschung; Russian Foundation for Basic Research","keywords":"Holocene; Radiocarbon dating; Geology; Sediment; Glacial period; Permafrost; Arctic; Pleistocene; Thermokarst; Total organic carbon; Biogenic silica; Paleolimnology; Physical geography; Oceanography; Sedimentary rock; Biogeochemical cycle; Geochemistry; Geomorphology; Paleontology; Ecology; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002056979,0.0002699729,0.0002315716,0.001255957,0.0007895104,0.0006553524,0.0002215046,0.0002491957,0.000574853],"category_scores_gemma":[0.000270669,0.0002839605,0.0002561082,0.001352991,0.0004015057,0.0003961665,0.0005739324,0.0001698039,0.0001268704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001392086,"about_ca_system_score_gemma":0.0007860793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1190245,"about_ca_topic_score_gemma":0.2352186,"domain_scores_codex":[0.9999257,0.000008593783,0.000008867102,0.00002189021,0.00001266459,0.00002229863],"domain_scores_gemma":[0.9998456,0.00001645168,0.00004781844,0.000008994112,0.00004555272,0.00003559752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001162217,0.00002370548,0.9821873,0.00004304284,0.00008586025,0.0002396409,0.00122189,0.0005027507,0.01013378,0.00003458563,0.00009393247,0.005317368],"study_design_scores_gemma":[0.000001008207,0.000005013192,0.9993671,0.000002888674,0.000008866671,0.00002156467,0.0001347742,0.0002441483,0.000134864,0.000003893495,0.00007456783,0.000001343854],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999619,0.00005537593,0.00002958085,0.000005030492,7.238007e-7,0.00000121704,0.0001547784,0.000002764976,0.000131613],"genre_scores_gemma":[0.999231,0.00005261691,0.00008173182,0.000006303262,0.000001386564,0.000003390269,0.0004362925,0.000002877489,0.0001844335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1190245,"threshold_uncertainty_score":0.2366634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06415301982887395,"score_gpt":0.3172570656183389,"score_spread":0.253104045789465,"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."}}