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Record W2554317204 · doi:10.1002/2016gl070817

Multidecadal increases in the Yukon River Basin of chemical fluxes as indicators of changing flowpaths, groundwater, and permafrost

2016· article· en· W2554317204 on OpenAlexaboutno aff
R. Toohey, Nicole M. Herman‐Mercer, Paul F. Schuster, Edda Mutter, Joshua C. Koch

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostTributaryDrainage basinHydrology (agriculture)Climate changeGroundwaterPrecipitationFlux (metallurgy)Environmental scienceStructural basinGeologyWeatheringPhysical geographyOceanographyGeochemistryGeomorphologyGeography

Abstract

fetched live from OpenAlex

Abstract The Yukon River Basin, underlain by discontinuous permafrost, has experienced a warming climate over the last century that has altered air temperature, precipitation, and permafrost. We investigated a water chemistry database from 1982 to 2014 for the Yukon River and its major tributary, the Tanana River. Significant increases of Ca, Mg, and Na annual flux were found in both rivers. Additionally, SO 4 and P annual flux increased in the Yukon River. No annual trends were observed for dissolved organic carbon (DOC) from 2001 to 2014. In the Yukon River, Mg and SO 4 flux increased throughout the year, while some of the most positive trends for Ca, Mg, Na, SO 4 , and P flux occurred during the fall and winter months. Both rivers exhibited positive monthly DOC flux trends for summer (Yukon River) and winter (Tanana River). These trends suggest increased active layer expansion, weathering, and sulfide oxidation due to permafrost degradation throughout the Yukon River Basin.

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 score0.890
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.032
GPT teacher head0.284
Teacher spread0.252 · 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

Citations162
Published2016
Admission routes1
Has abstractyes

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