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Record W2129729715 · doi:10.1139/cjes-2012-0151

Late Holocene glacial activity at Bromley Glacier, Cambria Icefield, northern British Columbia Coast Mountains, Canada

2013· article· en· W2129729715 on OpenAlexafffundvenueabout
Kira M. Hoffman, Dan J. Smith

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHoloceneGeologyGlacierIce fieldGlacial periodRadiocarbon datingPhysical geographyGlacier mass balanceGeomorphologyOceanographyPaleontologyGeography

Abstract

fetched live from OpenAlex

Retreating and downwasting glaciers in the British Columbia Coast Mountains are exposing the remains of forests buried during Holocene-age glacial advances. Despite recent progress in discerning the extent of these advances in the Pacific and Kitimat ranges of the southern and central Coast Mountains, comparatively little is known about the character of these advances in the Boundary Ranges of northwestern British Columbia. This research uses dendroglaciologic and radiocarbon analyses to describe late Holocene glacial advances at Bromley Glacier in the Cambria Icefield area. Four intervals of glacial expansion were identified at ca. 2470–2410, 1850, 1450, and 830 14C years BP. Absent were wood remains associated with mid-Holocene episodes of glacier expansion recorded at nearby sites. The late Holocene deposits described at Bromley Glacier are contemporaneous with those found at other glaciers in the southern Boundary Ranges and contribute to a growing understanding of the synchronous response of glaciers in this region to mass balance fluctuations during the Holocene.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.198
Teacher spread0.186 · 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

Citations9
Published2013
Admission routes4
Has abstractyes

Explore more

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