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Record W2721897552 · doi:10.1017/qua.2017.30

Age of some Pleistocene interglacial beds and associated fossils in eastern Beringia defined by fission tracks in glass shards of Chester Bluff tephra

2017· article· en· W2721897552 on OpenAlexafffundabout
John A. Westgate, Nicholas J.G. Pearce

Bibliographic record

VenueQuaternary Research · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTephraInterglacialGeologyPleistoceneFission track datingPaleontologyTephrochronologyVolcanoZircon

Abstract

fetched live from OpenAlex

Abstract Application of the glass fission-track dating method to Chester Bluff tephra (CBt), exposed in loess deposits at Chester Bluff along the Yukon River in east-central Alaska, has clarified the age of the immediately underlying fossiliferous interglacial bed. Surprise Creek tephra (SZt), at site CRH47 in the northern Old Crow basin of the Yukon Territory, is a correlative of CBt so that the new age information on CBt can also be applied to the interglacial sediments below SZt. Two independent age determinations were obtained on CBt, 243±28 ka and 249±26 ka, giving a weighted mean age and error of 246±19 ka. Therefore, the closely associated interglacial bed belongs to the early part of Marine Oxygen Isotope Stage (MIS) 7. The stratigraphy and paleoenvironmental setting of SZt show that deposition of the tephra occurred soon after interglacial conditions, when the climate became colder, probably between MIS 7.5 and 7.4, that is, slightly younger than the mean fission-track age, but within the 1σ uncertainty. This result tightly constrains the age of the rich mammalian faunal assemblage found at and just below SZt at the CRH47 site.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.013
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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

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 head0.069
GPT teacher head0.341
Teacher spread0.273 · 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

Citations7
Published2017
Admission routes3
Has abstractyes

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