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Record W4403690387 · doi:10.1002/ppp.2255

Recent Advances (2018–2023) and Research Opportunities in the Study of Groundwater in Cold Regions

2024· article· en· W4403690387 on OpenAlexafffund
Jean‐Michel Lemieux, Andrew Frampton, Philippe Fortier

Bibliographic record

VenuePermafrost and Periglacial Processes · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversité LavalCenter for Northern Studies
FundersSentinelle Nord, Université LavalBolincentret för klimatforskning, Stockholms UniversitetNatural Sciences and Engineering Research Council of CanadaNorges ForskningsrådCanada First Research Excellence FundSvenska Forskningsrådet FormasUniversité Laval
KeywordsPermafrostGroundwaterGeologyEarth scienceHydrology (agriculture)Physical geographyGeotechnical engineeringGeographyOceanography

Abstract

fetched live from OpenAlex

ABSTRACT Increasing greenhouse gas levels drive extensive changes in Arctic and cold‐dominated environments, leading to a warmer, more humid, and variable climate. Associated permafrost thaw creates new groundwater flow paths in cold regions that are causing unprecedented environmental changes. This review of recent advances in groundwater research in cold environments has revealed that a new paradigm is emerging where groundwater is at the center of these changes. Groundwater flow and associated heat and solute transport are now used as a basis to understand hydrological changes, permafrost dynamics, water quality, integrity of infrastructure along with ecological impacts. Although major advances have been achieved in cold regions' cryohydrogeological research, the remaining knowledge gaps are numerous. For example, groundwater as a drinking water source is poorly documented despite its social importance. Lateral transport processes for carbon and contaminants are still inadequately understood. Numerical models are improving, but the highly complex physical‐ecological changes occurring in the arctic involve coupled thermal, hydrological, hydrogeological, mechanical, and geochemical processes that are difficult to represent and hamper quantitative analysis and limit predictive capacity. Systematic long‐term observatories where measurements involving groundwater are considered central are needed to help resolve these research gaps. Innovative transdisciplinary research will be critical to comprehend and predict these complex transformations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.478
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.189
GPT teacher head0.350
Teacher spread0.161 · 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.

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

Citations13
Published2024
Admission routes2
Has abstractyes

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