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Record W2069500956 · doi:10.1029/2009eo060004

Investigating Age Resolution in Laser Ablation Geochronology: Workshop on Data Handling in LA‐ICP‐MSU‐Th‐Pb Geochronology; Vancouver, British Columbia, Canada, 12–13 July 2008

2009· article· en· W2069500956 on OpenAlexaffabout
Matthew Horstwood, Jan Košler, Simon E. Jackson, Norman J. Pearson, Paul Sylvester

Bibliographic record

VenueEos · 2009
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsMemorial University of NewfoundlandGeological Survey of Canada
Fundersnot available
KeywordsGeochronologyLaser ablationThoriumGeologyUraniumGeochemistryLaserMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) uranium‐thorium‐lead (U‐Th‐Pb) dating is an increasingly popular approach for determining the age of mineral grains and the timing of geological events. The spatial resolution offered by this technique allows detailed investigations of complex igneous and metamorphic processes, and the speed of data capture allows vast amounts of information to be gathered rapidly. Laser ablation U‐Th‐Pb dating is therefore becoming an increasingly influential technique to the geochronology community, providing cost‐effective and ready access to age data for laboratories and end users worldwide. However, complications in acquiring, processing, and interpreting data can lead to inaccurate age information entering the literature. With the numbers of practitioners expanding rapidly, the need to standardize approaches and resolve difficulties (particularly involving the subjectivity in processing laser ablation U‐Th‐Pb data) is becoming important.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.704
Threshold uncertainty score0.589

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0020.002
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.022
GPT teacher head0.226
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations8
Published2009
Admission routes2
Has abstractyes

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