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Record W3161496277 · doi:10.1130/g48386.1

First U-Pb dating of fossilized soft tissue using a new approach to paleontological chronometry

2021· article· en· W3161496277 on OpenAlexaff
Heriberto Rochín-Bañaga, Donald W. Davis, Tobías Schwennicke

Bibliographic record

VenueGeology · 2021
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiagenesisGeologyPaleontologyStratigraphyHorizonGeochemistryTectonics

Abstract

fetched live from OpenAlex

Abstract Previous U-Pb dating of fossils has had only limited success because of low uranium content and abundance of common Pb as well as element mobility during late diagenesis. We report the first accurate U-Pb dating of fossilized soft tissue from a Pliocene phosphatized bivalve mold using laser ablation–inductively coupled mass spectrometry (LA-ICPMS). The fossilized soft tissue yields a diagenetic U-Pb age of 3.16 ± 0.08 Ma, which is consistent with its late Pliocene stratigraphy and similar to the oldest U-Pb age measured on accompanying shark teeth. Phosphate extraclasts give a distinctly older age of 5.1 ± 1.7 Ma, indicating that they are likely detrital and may have furnished P, promoting phosphatization of the mold. The U-Pb ages reported here along with stratigraphic constraints suggest that diagenesis occurred shortly after the death of the bivalve and that the U-Pb system in the bivalve mold remained closed until the present. Shark teeth collected from the same horizon show variable resetting due to late diagenesis. Data were acquired as line scans in order to exploit the maximum Pb/U variation and were regressed as counts, rather than ratios, in three-dimensional space using a Bayesian statistical method.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.567
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0000.000
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 head0.048
GPT teacher head0.274
Teacher spread0.226 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations21
Published2021
Admission routes1
Has abstractyes

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