MétaCan
Menu
Back to cohort
Record W3036477547 · doi:10.1177/0959683620941073

Are there enormous age-trends in stable carbon isotope ratios of oak tree rings?

2020· article· en· W3036477547 on OpenAlexfundno aff
Danny McCarroll, Josie E. Duffy, Neil J. Loader, Giles Young, D. E. Davies, Daniel Miles, Christopher Bronk Ramsey

Bibliographic record

VenueThe Holocene · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNatural Environment Research CouncilSight Research UKLeverhulme Trust
KeywordsDendrochronologyStable isotope ratioIsotopes of carbonRadiocarbon datingSeries (stratigraphy)DendroclimatologyPhysical geographyIsotopeClimatologyCarbon fibersAtmospheric sciencesEnvironmental scienceGeologyGeographyMathematicsPaleontologyNuclear physicsPhysicsAlgorithm

Abstract

fetched live from OpenAlex

We test a recent prediction that stable carbon isotope ratios from UK oaks will display age-trends of more than 4‰ per century by measuring >5400 carbon isotope ratios from the late-wood alpha-cellulose of individual rings from 18 modern oak trees and 50 building timbers spanning the 9th-21st centuries. After a very short (c.5 years) juvenile phase with slightly elevated values, the number of series that show rising and falling trends is almost equal (33:35) and the average trend is almost zero. These results are based upon measuring and averaging the trends in individual time-series; the 'mean of the slopes' approach. We demonstrate that the more conventional 'slope of the mean' approach can produce strong but spurious 'age-trends' even when the constituent series are flat, with zero slope and zero variance. We conclude that it is safe to compile stable carbon isotope chronologies from UK oaks without de-trending. The isotope chronologies produced in this way are not subject to the 'segment length curse', which applies to growth measurements, such as ring width or density, and have the potential to retain very long-term climate signals.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.538

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.235
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations11
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueThe HoloceneSame topicTree-ring climate responsesFrench-language works237,207