MétaCan
Menu
Back to cohort
Record W2077883063 · doi:10.1029/2007gl030216

Increased groundwater to stream discharge from permafrost thawing in the Yukon River basin: Potential impacts on lateral export of carbon and nitrogen

2007· article· en· W2077883063 on OpenAlexaboutno aff
Michelle A. Walvoord, Robert G. Striegl

Bibliographic record

VenueGeophysical Research Letters · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostGroundwaterThermokarstStreamflowDissolved organic carbonEnvironmental scienceHydrology (agriculture)ArcticDrainage basinSubarctic climateGroundwater dischargeGroundwater flowSurface waterClimate changeInfiltration (HVAC)OceanographyGeologyAquiferGeographyEnvironmental engineering

Abstract

fetched live from OpenAlex

Arctic and subarctic watersheds are undergoing climate warming, permafrost thawing, and thermokarst formation resulting in quantitative shifts in surface water –groundwater interaction at the basin scale. Groundwater currently comprises almost one fourth of Yukon River water discharged to the Bering Sea and contributes 5–10% of the dissolved organic carbon (DOC) and nitrogen (DON) and 35–45% of the dissolved inorganic carbon (DIC) and nitrogen (DIN) loads. Long‐term streamflow records (>30 yrs) of the Yukon River basin indicate a general upward trend in groundwater contribution to streamflow of 0.7–0.9%/yr and no pervasive change in annual flow. We propose that the increases in groundwater contributions were caused predominately by climate warming and permafrost thawing that enhances infiltration and supports deeper flowpaths. The increased groundwater fraction may result in decreased DOC and DON and increased DIC and DIN export when annual flow remains unchanged.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.285
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations630
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicClimate change and permafrostFrench-language works237,207