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Record W2513355335 · doi:10.1016/j.yqres.2016.06.004

Identification of a Kulshan caldera correlative tephra in the Palouse loess of Washington State, northwest USA

2016· article· en· W2513355335 on OpenAlexaff
Georgina E. King, Nicholas J.G. Pearce, Helen M. Roberts, Vicki Smith, John A. Westgate, David R. Gaylord, Mark R. Sweeney

Bibliographic record

VenueQuaternary Research · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Toronto
FundersAberystwyth University
KeywordsTephraGeologyCalderaRhyoliteVolcanoLoessMagmaDaciteGeochemistryLavaQuaternaryPleistoceneGeomorphologyPaleontologyVolcanic rock

Abstract

fetched live from OpenAlex

Abstract The Kulshan caldera formed at ∼1.15 Ma on the present-day site of Mt. Baker, Washington State, northwest USA and erupted a compositionally zoned (dacite-rhyolite) magma and a correlative eruptive, the Lake Tapps tephra. This tephra has previously been described, but only from the Puget Lowland of NW Washington. Here an occurrence of a Kulshan caldera correlative tephra is described from the Quaternary Palouse loess at the Washtucna site (WA-3). Site WA-3 is located in east-central Washington, ∼340 km southeast of the Kulshan caldera and ∼300 km east-southeast of the Lake Tapps occurrence in the Puget Lowland. Major- and trace element chemistry and location of the deposit at Washtucna within reversed polarity sediments indicates that it is not correlative with the Mesa Falls, Rockland, Bishop Ash, Lava Creek B or Huckleberry Ridge tephras. Instead the Washtucna deposit is related to the Lake Tapps tephra by fractional crystallisation, but is chemically distinct, a consequence of its eruption from a compositionally zoned magma chamber. The correlation of the Washtucna occurrence to the Kulshan caldera-forming eruption indicates that it had an eruptive volume exceeding 100 km 3 , and that its tephra could provide a valuable early-Pleistocene chronostratigraphic marker in the Pacific Northwest.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.999

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 studies0.0000.000
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 head0.050
GPT teacher head0.303
Teacher spread0.253 · 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.

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
Published2016
Admission routes1
Has abstractyes

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