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Record W4412432568 · doi:10.1016/j.dendro.2025.126385

ISODATE – Software for stable isotope dendrochronology

2025· article· en· W4412432568 on OpenAlexfundno aff
D. E. Davies, Neil J. Loader, Danny McCarroll, D. H. Miles, Christopher Bronk Ramsey

Bibliographic record

VenueDendrochronologia · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersUK Research and InnovationSocial Sciences and Humanities Research Council of CanadaSwansea UniversitySocial Sciences and Humanities Research CouncilMarsden FundArts and Humanities Research Council
KeywordsDendrochronologyStable isotope ratioGeologyArchaeologyEnvironmental scienceGeographyNuclear physicsPhysics

Abstract

fetched live from OpenAlex

ISODATE is a complete dating package for stable oxygen isotope dendrochronology that offers a user-friendly workspace for processing, crossmatching and precisely dating stable isotope chronologies. ISODATE provides the first standardisation of approach for isotope laboratories and the heritage sector for dating and the reporting of dates. The software produces downloadable figures and CSV files containing series alignments and statistical results. The application is freely and publicly available online (isodate.swansea.ac.uk). A manual and guided example accompanies the software. It is hoped that community-led refinements and additional reference chronologies will be added to ISODATE as the technique develops and is adopted more widely.

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)0.005
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.184
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0020.001
Scholarly communication0.0050.006
Open science0.0040.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.1840.130

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 head0.265
Teacher spread0.248 · 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
GenreSoftware

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

Citations5
Published2025
Admission routes1
Has abstractyes

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