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Glacier Distributions and Climate in the Canadian Rockies

2004· article· en· W2203121082 on OpenAlex
J. M. Shea, Shawn J. Marshall, Joanne M. Livingston

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Space Research AssociationUniversity of Calgary
KeywordsGlacierPrecipitationClimatologyPhysical geographyGlacier mass balanceClimate changeGlacial periodExtrapolationGeologyDigital elevation modelElevation (ballistics)Environmental scienceGeographyMeteorologyGeomorphologyOceanography

Abstract

fetched live from OpenAlex

Glacier-climate relationships in the Canadian Rockies have been documented previously through mass-balance studies of individual glaciers and local meteorological parameters. In terms of regional significance, however, the relationship between the areal distribution of glaciers and regional climate is perhaps more important in evaluating large-scale responses to climate forcings. The purpose of the current study is to establish which climate variables are responsible for the observed distribution of glaciers. Using a 1:50,000 digitized coverage of glaciers in the Canadian Rockies, a 1-km resolution Digital Elevation Model (DEM) and climate normals from 88 stations throughout the study area, the authors examine the correlation between climate variables and the distribution of glacial ice in the Canadian Rockies. Through the construction of climatic lapse rates, sea-surface interpolation, and subsequent extrapolation based on the DEM, simple cell climatologies that reflect both the altitudinal and regional variations in temperature and precipitation are developed for the study area. Normalized Ice Coverage values prescribed for the study cells from the digitized coverage are then examined through a statistical framework which suggests that spring precipitation, annual temperatures, and winter precipitation are the strongest predictors of glacier distributions in the Canadian Rockies.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

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

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 head0.051
GPT teacher head0.298
Teacher spread0.247 · 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