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Record W1171502957

103. Queen Elizabeth Islands: Water Balance Investigations

2004· article· en· W1171502957 on OpenAlexaboutno aff
Kathy L. Young, Ming‐ko Woo

Bibliographic record

VenueIAHS-AISH publication · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsSnowmeltSurface runoffStreamflowWater balanceArcticSnowGlacierEnvironmental sciencePermafrostHydrology (agriculture)WetlandPhysical geographyGeologyDrainage basinOceanographyGeographyEcologyGeomorphology
DOInot available

Abstract

fetched live from OpenAlex

The Queen Elizabeth Islands, Canada, possess environments typical of the Arctic region. Polar deserts are the most extensive. The water budget of its basins is dominated by snowfall and snowmelt-generated runoff, giving rise to a nival regime of streamflow. Polar oases are warmer areas with enhanced evaporation and more variable flow than the deserts. Glaciers and late-lying snow cover provide late season high flows but experience low evaporation, though ice accumulation and melt constitute important storage changes. Wetlands have high flows similar to the polar desert, but evaporation reduces summer runoff, producing the distinctive wetland streamflow regime. Runoff ratios are high for polar deserts and glacierized basins, but the vegetated polar oases and wetlands exhibit ratios more comparable to the Low Arctic. A recent attempt to model a circumpolar water budget does not yield quantities that match field results, and further research is needed to refine the regional water balance.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0310.008

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 head0.030
GPT teacher head0.235
Teacher spread0.205 · 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

Citations13
Published2004
Admission routes1
Has abstractyes

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