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Record W2078486947 · doi:10.1657/1938-4246-41.2.246

Modeling Ablation on Place Glacier, British Columbia, from Glacier and Off-glacier Data Sets

2009· article· en· W2078486947 on OpenAlexafffundabout
D. Scott Munro, Marzena Marosz-Wantuch

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Toronto
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric Sciences
KeywordsGlacierGeologySnowGlacier mass balanceClimatologyAccumulation zoneAtmospheric sciencesMeteorologyIce streamCryosphereGeomorphologyGeography

Abstract

fetched live from OpenAlex

The results of two simulations of hourly ablation, from late July to September 2002, at a site on the Place Glacier are described. First, ablation is modeled from a data set collected at the glacier site; second, from a data set collected off-glacier at a site below the glacier tongue. The glacier data set simulations, based as they are on global and reflected short-wave radiation measurements, a net long-wave radiation model and the bulk turbulent heat transfer approach, provides a reasonably good simulation of cumulative ablation, amounting to almost 1.2 m during the experimental period, mostly due to melting out of the preceding winter snowpack. Average melt component flux densities due to net short-wave radiation, net long-wave radiation, sensible heat and latent heat due to moisture exchange are 93.1, −22.6, 14.4 and 3.91 W m−2, respectively, during this time. The glacier site data are also used to fit a snow albedo model to albedo measurements for old and new snow cover. The albedo model is then used in the second simulation, which is based on global radiation measurements, a similar net long-wave radiation model, and a heat transfer approach in which turbulent mixing due to katabatic and geostrophic flow is parameterized from the off-glacier temperature data. The second simulation scheme performs best if the katabatic component of the parameterization scheme is suppressed because the wind regime at the glacier site appears to be intermittent, but the scheme itself is based upon the idea of a continuously flowing glacier wind.

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 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 score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.084
GPT teacher head0.310
Teacher spread0.226 · 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

Citations12
Published2009
Admission routes3
Has abstractyes

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