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Record W2895322433 · doi:10.1029/2018gl079660

Fluvial Response to a Period of Hydrometeorological Change and Landscape Disturbance in the Canadian High Arctic

2018· article· en· W2895322433 on OpenAlexafffundabout
C. R. Beel, Scott F. Lamoureux, John F. Orwin

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsAlberta Environment and Protected AreasQueen's University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorArcticNet
KeywordsHydrometeorologyFluvialPermafrostArcticSedimentHydrology (agriculture)PluvialDisturbance (geology)Environmental scienceClimate changeGeologyChannel (broadcasting)Sediment transportPrecipitationGeomorphologyOceanographyGeographyMeteorology

Abstract

fetched live from OpenAlex

Abstract Records of fluvial suspended sediment fluxes are sensitive indicators of hydrometeorological and permafrost change. Here we document the watershed‐scale suspended sediment flux response to a period of hydrometeorological change and landscape disturbance in two High Arctic rivers. Net in‐channel and extra‐channel sediment storage and changing hydrometeorological conditions dampen the downstream transport of increased sediment delivery from localized permafrost slope disturbances. Our results show that the impact of permafrost disturbance is likely a smaller effect than a shift toward a pluvially (rainfall) dominated hydrological regime in these environments. Suspended sediment transport is energy limited under contemporary hydrometeorological conditions, and the transition from a nival to pluvial dominated flow and sediment transfer regime will likely accelerate landscape change in the High Arctic.

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)0.001
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 score0.053
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.079
GPT teacher head0.299
Teacher spread0.219 · 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

Citations30
Published2018
Admission routes3
Has abstractyes

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