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Record W2009623812 · doi:10.1029/2009gl039225

Evolution of shallow groundwater flow systems in areas of degrading permafrost

2009· article· en· W2009623812 on OpenAlexaff
Victor Bense, Grant Ferguson, Henk Kooi

Bibliographic record

VenueGeophysical Research Letters · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsPermafrostGroundwaterGroundwater flowHydrogeologyAquiferWater tableHydrology (agriculture)GeologyGroundwater dischargeCurrent (fluid)STREAMSEnvironmental scienceFlow (mathematics)ArcticSubsurface flowGroundwater modelOceanographyGeotechnical engineering

Abstract

fetched live from OpenAlex

The recent increase in fresh‐water discharge during low‐flow conditions as observed in many (sub‐)Arctic Rivers has been attributed to a reactivation of groundwater flow systems caused by permafrost degradation. Hydrogeological simulations show how groundwater flow conditions in an idealized aquifer system evolve on timescales of decades to centuries in response to climate warming scenarios as progressive lowering of the permafrost table establishes a growing shallow groundwater flow system. Ultimately, disappearance of residual permafrost at depth causes a sudden establishment of deep groundwater flow paths. The projected shifts in groundwater flow conditions drive characteristic non‐linear trends in the evolution of increasing groundwater discharge to streams. Although the subsurface distribution of ice will markedly influence the system response, current modeling results suggest that late‐stage accelerations in base flow increase of streams and rivers, are to be expected, even if surface air temperatures stabilize at the current levels in the near future.

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 score0.008
Threshold uncertainty score0.015

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 head0.057
GPT teacher head0.291
Teacher spread0.235 · 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

Citations236
Published2009
Admission routes1
Has abstractyes

Explore more

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