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Record W2101351605 · doi:10.1017/s0033822200042375

Towards a Radiocarbon Calibration for Oxygen Isotope Stage 3 Using New Zealand Kauri (<i>Agathis Australis</i>)

2007· article· en· W2101351605 on OpenAlexfundno aff
Chris Turney, L.K. Fifield, Jonathan Palmer, Alan Hogg, Mike Baillie, R. F. Galbraith, John C. Ogden, Andrew M. Lorrey, S.G. Tims

Bibliographic record

VenueRadiocarbon · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersAustralian Research CouncilQueen's UniversityUniversity of Wollongong
KeywordsRadiocarbon datingSubfossilCalibration curveCalibrationChronologyHoloceneGeologyPaleontologyIsotopes of oxygenAbsolute datingArchaeologyPhysical geographyEnvironmental scienceGeographyPhysicsGeochemistryChemistry

Abstract

fetched live from OpenAlex

It is well known that radiocarbon years do not directly equate to calendar time. As a result, considerable effort has been devoted to generating a decadally resolved calibration curve for the Holocene and latter part of the last termination. A calibration curve that can be unambiguously attributed to changes in atmospheric 14 C content has not, however, been generated beyond 26 kyr cal BP, despite the urgent need to rigorously test climatic, environmental, and archaeological models. Here, we discuss the potential of New Zealand kauri ( Agathis australis ) to define the structure of the 14 C calibration curve using annually resolved tree rings and thereby provide an absolute measure of atmospheric 14 C. We report bidecadally sampled 14 C measurements obtained from a floating 1050-yr chronology, demonstrating repeatable 14 C measurements near the present limits of the dating method. The results indicate that considerable scope exists for a high-resolution 14 C calibration curve back through OIS-3 using subfossil wood from this source.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.285
Teacher spread0.247 · 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 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

Citations27
Published2007
Admission routes1
Has abstractyes

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