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Record W4393381849 · doi:10.1130/b37321.1

Recommendations for the reporting and interpretation of isotope dilution U-Pb geochronological information

2024· article· en· W4393381849 on OpenAlexaff
Daniel J. Condon, Blair Schoene, Mark D. Schmitz, Urs Schaltegger, Ryan B. Ickert, Yuri Amelin, Lars Eivind Augland, Kevin R. Chamberlain, Drew S. Coleman, James N. Connelly, Fernando Corfú, James L. Crowley, Joshua H.F.L. Davies, Steven W. Denyszyn, Michael P. Eddy, Sean P. Gaynor, Larry M. Heaman, Magdalena H. Huyskens, Sandra L. Kamo, Jennifer Kasbohm, C. Brenhin Keller, S. A. MacLennan, Noah M. McLean, Stephen R. Noble, Maria Ovtcharova, André Navin Paul, Jahandar Ramezani, Matt Rioux, Diana Sahy, James S. Scoates, Dawid Szymanowski, Simon Tapster, Marion Tichomirowa, Corey J. Wall, Jörn‐Frederik Wotzlaw, Chuan Yang, Qing‐Zhu Yin

Bibliographic record

VenueGeological Society of America Bulletin · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of TorontoUniversity of AlbertaUniversity of British ColumbiaMemorial University of NewfoundlandUniversité du Québec à Montréal
FundersNatural Environment Research CouncilEuropean Science FoundationSight Research UKNational Science Foundation
KeywordsGeologyIsotope dilutionInterpretation (philosophy)IsotopeGeochemistryEarth scienceMass spectrometryNuclear physics

Abstract

fetched live from OpenAlex

Abstract U-Pb geochronology by isotope dilution–thermal ionization mass spectrometry (ID-TIMS) has the potential to be the most precise and accurate of the deep time chronometers, especially when applied to high-U minerals such as zircon. Continued analytical improvements have made this technique capable of regularly achieving better than 0.1% precision and accuracy of dates from commonly occurring high-U minerals across a wide range of geological ages and settings. To help maximize the long-term utility of published results, we present and discuss some recommendations for reporting ID-TIMS U-Pb geochronological data and associated metadata in accordance with accepted principles of data management. Further, given that the accuracy of reported ages typically depends on the interpretation applied to a set of individual dates, we discuss strategies for data interpretation. We anticipate that this paper will serve as an instructive guide for geologists who are publishing ID-TIMS U-Pb data, for laboratories generating the data, the wider geoscience community who use such data, and also editors of journals who wish to be informed about community standards. Combined, our recommendations should increase the utility, veracity, versatility, and “half-life” of ID-TIMS U-Pb geochronological data.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.233
Teacher spread0.216 · 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.

Study designOther design
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

Citations29
Published2024
Admission routes1
Has abstractyes

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