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Record W2478134162 · doi:10.2166/nh.2003.0028

Thermo-hydrological Responses to an Exceptionally Warm, Dry Summer in a High Arctic Environment

2003· article· en· W2478134162 on OpenAlexafffundabout
Kathy L. Young, Ming‐ko Woo

Bibliographic record

VenueHydrology research · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsMcMaster UniversityYork University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scienceArcticSnowSurface runoffClimate changeWetlandClimatologyPermafrostStructural basinMoistureHydrology (agriculture)EvaporationWater tableTable (database)Atmospheric sciencesOceanographyGeologyEcologyGeographyGroundwaterMeteorology

Abstract

fetched live from OpenAlex

1998 was a very warm year for Canada and the High Arctic was no exception. A typical area was Resolute, Cornwallis Island, Nunavut, where the thaw season was extended and the thawing degree-days were larger than normal. The warm summer was accompanied by early spring melt and low rainfall. This study documents the thermo-hydrological responses including warming of the top soil, deepening of the active layer, alteration of the evaporation pattern, adjustment of the water table positions and runoff. The presence of semi-permanent snowbanks and patchy wetlands buffer some local sites from the warm and dry summer conditions. This and other studies show that the cryospheric and hydrologic systems may or may not recover quickly from the year to year variations in the climate, depending on how readily the storages (snow, ice and basin moisture) can be replenished. In view of the cumulative effects of storage depletion under climatic warming, short-term studies on thermo-hydrological behaviour in the Arctic provide a useful but insufficient analogue to capture the climatic change impacts.

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 score0.044
Threshold uncertainty score0.088

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 studies0.0010.000
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 head0.151
GPT teacher head0.346
Teacher spread0.195 · 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

Citations26
Published2003
Admission routes3
Has abstractyes

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