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Record W2059055994 · doi:10.1016/j.yqres.2014.07.001

Distinction between the Youngest Toba Tuff and Oldest Toba Tuff from northern Sumatra based on the area density of spontaneous fission tracks in their glass shards

2014· article· en· W2059055994 on OpenAlexafffund
John A. Westgate, Nicholas J.G. Pearce, Emma Gatti, Hema Achyuthan

Bibliographic record

VenueQuaternary Research · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTephraGeologyFission track datingRange (aeronautics)GeochemistryVolcanoZirconMaterials science

Abstract

fetched live from OpenAlex

Abstract Determination of the area density of spontaneous fission tracks (ρ s ) in glass shards of Toba tephra is a reliable way to distinguish between the Youngest Toba Tuff (YTT) and the Oldest Toba Tuff (OTT). The ρ s values for YTT, uncorrected for partial track fading, range from 70 to 181 tracks/cm 2 with a weighted mean of 108 ± 5 tracks/cm 2 , based on 15 samples. Corrected ρ s values for YTT are in the range of 77–140 tracks/cm 2 with a weighted mean of 113 ± 8 tracks/cm 2 , within the range of uncorrected ρ s values. No significant difference in ρ s exists between YTT samples collected from marine and continental depositional settings. The uncorrected ρ s for OTT is 1567 ± 114 tracks/cm 2 so that confusion with YTT is unlikely. The ρ s values of the Toba tephra at Bori, Morgaon, and Gandhigram in northwestern India indicate a YTT identity, in agreement with geochemical data on their glass shards, the presence of multiple glass populations, and a glass fission-track age determination. Therefore, the view of others that OTT is present at these sites – and thereby indicates an early Pleistocene age for the associated Acheulean artifacts – is incorrect.

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)0.004
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 score0.063
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.058
GPT teacher head0.277
Teacher spread0.219 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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