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Record W2887357510 · doi:10.1139/cjes-2018-0015

Late Wisconsinan Cordilleran and Laurentide glaciation of the Peace River Valley east of the Rocky Mountains, British Columbia

2018· article· en· W2887357510 on OpenAlexafffundvenueabout
Gregory Hartman, John J. Clague, René W. Barendregt, Alberto V. Reyes

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of AlbertaUniversity of LethbridgeSimon Fraser UniversityGeological Survey of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyIce sheetWisconsin glaciationGlacial periodPaleontologyGeomorphologyIce streamOceanographyCryosphereSea ice

Abstract

fetched live from OpenAlex

In the past, researchers have disagreed over the maximum extent of the Cordilleran Ice Sheet in the Peace River valley during the Late Wisconsinan. Some workers argued that Cordilleran ice reached beyond the Rocky Mountains and briefly coalesced with the Laurentide Ice Sheet on the westernmost Interior Plains. In contrast, others asserted that Cordilleran ice did not reach beyond the eastern front of the Rocky Mountains. Stratigraphic interpretation of three sections within a Middle Wisconsinan paleovalley and re-examination of a previously published regional stratigraphic framework show that western-sourced ice (likely the Cordilleran Ice Sheet) extended east of the mountain front during the Late Wisconsinan, prior to the incursion of the Laurentide Ice Sheet into the area. This conclusion has implications for Cordilleran Ice Sheet reconstruction and modelling, and provides insight into the interactions between the Cordilleran and Laurentide ice sheets during the last glaciation.

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 score0.023
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.203
Teacher spread0.189 · 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

Citations24
Published2018
Admission routes4
Has abstractyes

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