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Record W7024521660

Spatial variation of snow vapour fluxes and melt in the Coldstream Basin, Okanagan, BC

2008· article· en· W7024521660 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Legal Studies and Society
Canadian institutionsnot available
Fundersnot available
KeywordsSnowTransectSnowmeltElevation (ballistics)Atmosphere (unit)Energy balanceWater vaporPrecipitationMagnitude (astronomy)
DOInot available

Abstract

fetched live from OpenAlex

The Okanagan Basin is very likely to experience increasing water stress under projected climate change scenarios as a result of lower winter snowpacks, increasing frequency of mid-winter melt events and earlier freshets, reducing the amount of water available during the summer when demand is highest. Relatively little is known about the high elevation snow that is responsible for maintaining river discharges in this region into the summer. Snow energy and mass balance processes were studied along an elevational transect of forested and open sites in the Coldstream basin in the late winter and spring of 2007 to address this knowledge gap. SWE losses to sublimation/evaporation averaged 0.6mm and 0.8mm/day for the high and mid elevation sites respectively, with maximums exceeding 3mm/day. Correlations between gravimetric and bulk aerodynamic estimates of vapour loss and melt were generally high, with the exception of warm, windy conditions, where vapour fluxes were underestimated by the standard bulk aerodynamic methods. Roughness lengths were found to be at least an order of magnitude larger than those typically used in snow energy balance studies. The vapour fluxes were placed into magnitude classes, and related to prevailing synoptic climate conditions, gathered from upper atmosphere data gathered at the Kelowna Airport.

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 score0.236
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.023
GPT teacher head0.233
Teacher spread0.210 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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Same venueWestern CEDAR (Western Washington University)Same topicHistorical Legal Studies and SocietyFrench-language works237,207