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Community‐Derived Standards for <scp>LA</scp>‐<scp>ICP</scp>‐<scp>MS</scp> U‐(Th‐)Pb Geochronology – Uncertainty Propagation, Age Interpretation and Data Reporting

2016· article· en· W2342124398 on OpenAlexaff
Matthew Horstwood, Jan Košler, George E. Gehrels, Simon E. Jackson, Noah M. McLean, Chad Paton, Norman J. Pearson, Keith Sircombe, Paul Sylvester, Pieter Vermeesch, James F. Bowring, Daniel J. Condon, Blair Schoene

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsGeological Survey of Canada
FundersNatural Environment Research CouncilSight Research UKNational Science Foundation
KeywordsGeochronologyPopulationCalibrationComputer scienceStatisticsOverprintingGeologyMineralogyData miningMathematicsGeochemistryMedicine

Abstract

fetched live from OpenAlex

The LA ‐ ICP ‐ MS U‐(Th‐)Pb geochronology international community has defined new standards for the determination of U‐(Th‐)Pb ages. A new workflow defines the appropriate propagation of uncertainties for these data, identifying random and systematic components. Only data with uncertainties relating to random error should be used in weighted mean calculations of population ages; uncertainty components for systematic errors are propagated after this stage, preventing their erroneous reduction. Following this improved uncertainty propagation protocol, data can be compared at different uncertainty levels to better resolve age differences. New reference values for commonly used zircon, monazite and titanite reference materials are defined (based on ID ‐ TIMS ) after removing corrections for common lead and the effects of excess 230 Th. These values more accurately reflect the material sampled during the determination of calibration factors by LA ‐ ICP ‐ MS analysis. Recommendations are made to graphically represent data only with uncertainty ellipses at 2 s and to submit or cite validation data with sample data when submitting data for publication. New data‐reporting standards are defined to help improve the peer‐review process. With these improvements, LA ‐ ICP ‐ MS U‐(Th‐)Pb data can be considered more robust, accurate, better documented and quantified, directly contributing to their improved scientific interpretation.

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)0.040
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.960
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.050
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0180.013
Science and technology studies0.0040.003
Scholarly communication0.0060.004
Open science0.0090.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0300.041

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 head0.075
GPT teacher head0.360
Teacher spread0.285 · 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.

Study designNot applicable
DomainReporting
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

Citations1,002
Published2016
Admission routes1
Has abstractyes

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