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Record W3096939545 · doi:10.1029/2020gl088823

An Abrupt Aging of Dissolved Organic Carbon in Large Arctic Rivers

2020· article· en· W3096939545 on OpenAlexaff
Melissa Schwab, Robert Hilton, Peter A. Raymond, Negar Haghipour, Edwin Amos, Suzanne E. Tank, R. M. Holmes, Edward T. Tipper, Timothy I. Eglinton

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of AlbertaAurora College
FundersNatural Environment Research CouncilSight Research UKSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsPermafrostDissolved organic carbonTotal organic carbonArcticEnvironmental scienceRadiocarbon datingCarbon fibersOrganic matterCarbon cycleSoil carbonNitrateDrainage basinHydrology (agriculture)Physical geographyOceanographyGeologyEnvironmental chemistrySoil waterEcosystemSoil scienceGeographyEcologyChemistry

Abstract

fetched live from OpenAlex

Abstract Permafrost thaw in Arctic watersheds threatens to mobilize hitherto sequestered carbon. We examine the radiocarbon activity (F 14 C) of dissolved organic carbon (DOC) in the northern Mackenzie River basin. From 2003–2017, DOC‐F 14 C signatures (1.00 ± 0.04; n = 39) tracked atmospheric 14 CO 2 , indicating export of “modern” carbon. This trend was interrupted in June 2018 by the widespread release of aged DOC (0.85 ± 0.16, n = 28) measured across three separate catchment areas. Increased nitrate concentrations in June 2018 lead us to attribute this pulse of 14 C‐depleted DOC to mobilization of previously frozen soil organic matter. We propose export through lateral perennial thaw zones that occurred at the base of the active layer weakened by preceding warm summer and winter seasons. Although we are not yet able to ascertain the broader significance of this “anomalous” mobilization event, it highlights the potential for rapid and large‐scale release of aged carbon from permafrost.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.307
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations82
Published2020
Admission routes1
Has abstractyes

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