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Record W2107267521

Holocene Glacial History of the Bowser River Watershed, Northern Coast Mountains, British Columbia

2014· dissertation· en· W2107267521 on OpenAlexaboutno aff
Vikki Maria St-Hilaire

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsHoloceneGlacial periodWatershedArchaeologyGeographyPhysical geographyGeologyOceanographyGeomorphology
DOInot available

Abstract

fetched live from OpenAlex

Accelerated glacial recession and downwasting of glaciers in the Bowser River Watershed of the northern British Columbia Coast Mountains have exposed subfossil wood remains and laterally contiguous wood mat layers. To develop an understanding of Holocene glacial fluctuations in this region, field investigations were conducted in 2005, 2006 and 2013 at Frank Mackie, Charlie, Salmon and Canoe glaciers. These wood remains represent periods of Holocene glacier advance, when glaciers expanded and overwhelmed downvalley forests. Dendroglaciology and radiocarbon analyses revealed five intervals of glacial expansion: (1) a mid-Holocene advance at 5.7-5.1 ka cal. yr BP; (2) an early Tiedemann advance at 3.6-3.4 ka cal. yr BP; (3) a late Tiedemann advance at 2.7-2.4 ka cal. yr BP; (4) a First Millennium AD Advance at 1.8-1.6 ka cal. yr BP; and, (5) three advances during the Little Ice Age at 0.9-0.7, 0.5 and 0.2-0.1 ka cal. yr BP. These results provide new evidence for mid-Holocene glacier activity in northern British Columbia, as well as supporting previous research that Holocene glacier advances were episodic and regionally synchronous.

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 score0.013
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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

Citations3
Published2014
Admission routes1
Has abstractno

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