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Record W3180452746

Our Vanishing Glaciers: The Snows of Yesteryear and the Future Climate of the Mountain West

2017· book· en· W3180452746 on OpenAlexaboutno aff
Robert William Sandford

Bibliographic record

VenueUNU Collections (United Nations University) · 2017
Typebook
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsGlacierIce fieldPhysical geographyGeographySnowGeologyGlacier morphologyGlacial periodCoveIcebergMeltwaterIce sheetArchaeologyClimatologyOceanographyMeteorologyGeomorphologyIce streamCryosphereSea ice
DOInot available

Abstract

fetched live from OpenAlex

Written by one of the most respected experts in water and water-associated climate science and featuring stunning photography collected over the past four decades, Our Vanishing Glaciers explains and illustrates why water is such a unique substance and how it makes life on this planet possible. Focusing on the Columbia Icefield, the largest and most accessible mass of ice straddling the Continental Divide in western North America, and featuring photographs, illustrations, aerial surveys and thermal imaging collected over more than 40 years of the author’s personal observations, the book reveals the stunning magnitude of glacial ice in western Canada. Citing evidence to suggest that in the Canadian Rocky Mountain national parks alone, as many as 300 glaciers may have disappeared since 1920, this large-format, fully illustrated coffee table book graphically illustrates the projected rate of glacier recession in the mountain West over the rest of this century and serves as a profound testament to the beauty and importance of western Canada’s water, ice and snow.

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.074
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0220.005

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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
GenreOther

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

Citations1
Published2017
Admission routes1
Has abstractyes

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