{"id":"W4220913901","doi":"10.1029/2021jg006578","title":"Trapped Under Ice: Spatial and Seasonal Dynamics of Dissolved Organic Matter Composition in Tundra Lakes","year":2022,"lang":"en","type":"article","venue":"Journal of Geophysical Research Biogeosciences","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"High Magnetic Field Laboratory, Chinese Academy of Sciences; Division of Chemistry; Division of Materials Research; National High Magnetic Field Laboratory; National Science Foundation","keywords":"Dissolved organic carbon; Tundra; Arctic; Environmental science; Sea ice; Arctic ice pack; Biogeochemical cycle; Carbon cycle; Atmosphere (unit); Total organic carbon; Oceanography; Atmospheric sciences; Environmental chemistry; Geology; Chemistry; Ecology; Ecosystem; Geography; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001887287,0.0001540561,0.000224007,0.0006004311,0.0005242869,0.0005864643,0.0002203579,0.0002381327,0.0003443172],"category_scores_gemma":[0.0003367014,0.0001613488,0.0001624189,0.0007517418,0.0002704547,0.0002813937,0.0002826912,0.0001489587,0.00007330607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006641232,"about_ca_system_score_gemma":0.000299955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05487755,"about_ca_topic_score_gemma":0.08480518,"domain_scores_codex":[0.9998983,0.00001436352,0.000007686291,0.00004044013,0.00001503272,0.00002426418],"domain_scores_gemma":[0.9997343,0.00003355313,0.0001109656,0.00001256329,0.00006874999,0.00003982927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001637071,0.00002099842,0.9849927,0.00001328942,0.00006366271,0.00005953897,0.000429119,0.00014431,0.01172346,0.00001597006,0.00005175218,0.002321415],"study_design_scores_gemma":[0.000001016453,0.00001474764,0.9989597,0.000001953133,0.00000996676,0.00001943233,0.0002768863,0.0002404838,0.0003768211,0.000005730928,0.00009162449,0.000001690418],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996718,0.00006195522,0.0000259069,0.000006133251,0.000001050992,9.376512e-7,0.000136415,0.000002049607,0.00009378837],"genre_scores_gemma":[0.9995819,0.00003956724,0.00005918909,0.000008414083,0.000001907654,0.000002918561,0.0001971288,0.000001259486,0.0001077267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05487755,"threshold_uncertainty_score":0.1091163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01864277779423275,"score_gpt":0.2652726994748817,"score_spread":0.2466299216806489,"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."}}