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Record W6948286064 · doi:10.5066/p92izpid

Whole Rock Geochemistry and Uranium Lead Isotopic Data from the Dinwiddie Terrane, Virginia, USA

2023· dataset· en· W6948286064 on OpenAlexaboutno aff

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2023
Typedataset
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsUraniumTerraneIsotopes of uraniumIsotopic signatureIsotope geochemistryUranium oreIsotopeLead (geology)

Abstract

fetched live from OpenAlex

This data release includes whole rock geochemical data, and uranium-lead isotopic data collected by both Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) and Sensitive High Resolution Ion Microprobe-Reverse Geometry (SHRIMP-RG) methods. Whole rock geochemistry was collected by Activation Laboratories in Ancaster, Ontario. LA-ICP-MS data was collected at the PLASMA at the USGS in Denver, Colorado. SHRIMP-RG data was collected at the USGS-Stanford SHRIMP-RG in Palo Alto, California. Rock samples for all methods were collected by Mark Carter of the USGS. The whole rock geochemistry and uranium lead isotopic data constrain the age and origin of rocks in the newly defined Dinwiddie Terrane of eastern Virginia.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0680.052

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 head0.040
GPT teacher head0.247
Teacher spread0.207 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2023
Admission routes1
Has abstractyes

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