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Record W2565660515 · doi:10.1002/ppp.1931

Spatial and temporal dynamics of groundwater flow across a wet meadow, Polar Bear Pass, Bathurst island, Nunavut

2016· article· en· W2565660515 on OpenAlexafffundabout
Kathy L. Young, Harold-Alexis Scheffel, Anna Abnizova, John R. Siferd

Bibliographic record

VenuePermafrost and Periglacial Processes · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsYork University
FundersArcticNetAustralian Government
KeywordsTundraGroundwaterHydrology (agriculture)SnowmeltWetlandGroundwater flowPermafrostEnvironmental scienceWater tableWater levelWet seasonGeologySurface waterArcticAquiferSnowEcologyOceanographyGeomorphologyGeography

Abstract

fetched live from OpenAlex

Interest is growing about how groundwater supplies will shift in warming northern terrains. We evaluated the seasonal and spatial pattern of groundwater flow in a wet meadow bordered by a late-lying snowbed and tundra ponds at Polar Bear Pass, Bathurst Island (75.7°N, 98.7°W). A water budget approach signalled the relative importance of groundwater inflow to tundra ponds. Groundwater flow across the wet meadow was estimated using a modified Darcy's equation, which requires information on both water and frost tables, and hydraulic conductivity. These data were obtained from 2007 to 2009 along a series of water wells extending from a late-lying snowbed across the wet meadow to a nearby study pond. Groundwater fluxes across the wet meadow were limited in magnitude and duration in a warm/dry year (2007), when the late-lying snowbed was the main external water source, a response differing from rainy/cool years (2008 and 2009). Overall, seasonal water budgets indicate that groundwater fluxes were minimal in the wet meadow and an adjacent tundra pond. Late-lying snowbeds play a limited role in sustaining wet meadows and ponds here. Summer precipitation and evaporation continue to drive wet meadow and tundra pond hydrological response in low-gradient wetlands, especially in the post-snowmelt season. Copyright © 2016 John Wiley & Sons, Ltd.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.236
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 teacher head, not a consensus.

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

Citations17
Published2016
Admission routes3
Has abstractyes

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