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Reconstructing the advance and retreat dynamics of the central sector of the last Cordilleran Ice Sheet

2022· article· en· W4224235026 on OpenAlexaboutno aff
Helen E. Dulfer, Martin Margold, Christopher M. Darvill, Arjen P. Stroeven

Bibliographic record

VenueQuaternary Science Reviews · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyIce sheetIce streamGlacierLandformPhysical geographyGlacial periodGlacial landformWisconsin glaciationGlacier morphologyAntarctic sea iceLast Glacial MaximumSeabed gouging by iceCryosphereGeomorphologyClimatologySea iceMoraineGeography

Abstract

fetched live from OpenAlex

The advance of the Cordilleran Ice Sheet (CIS) towards its Last Glacial Maximum (LGM) configuration and its subsequent retreat remain poorly understood. We use the glacial landform record to determine ice dynamics for the central sector of the CIS in northern British Columbia, Canada, beneath the LGM ice divide. We classify seventy ice-flow indicator flowsets based on morphology, elevation, orientation and cross-cutting relationships into one of three stages, whereby stage 1 is oldest and stage 3 youngest. Combined with ice-contact geomorphology, our reconstruction highlights complex changes in ice flow over time as a result of ice divide migrations through the LGM and deglacial phases. The orientation and distribution of landforms indicates active post-LGM ice retreat westward through the Cassiar and Omineca mountains. We map the regional distribution of independent mountain glaciers, ice caps, and ice fields that regrew during a cooling event in the Late Glacial and show that some of these readvance glaciers were subsequently overrun by advancing outlet glaciers of the CIS. We use the cross-cutting relationship between readvance glaciers and CIS outlet glaciers and available chronological data to reconstruct the eastern CIS margin during the Late Glacial for the first time.

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)0.002
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 score0.017
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.250
Teacher spread0.227 · 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.

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

Citations12
Published2022
Admission routes1
Has abstractyes

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