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Record W4409754179 · doi:10.1111/arcm.13089

High‐resolution compound‐specific δ<sup>15</sup>N isotope dietary study of humans from the Scottish Mesolithic and Neolithic

2025· article· en· W4409754179 on OpenAlexafffund
Valentina Martinoia, Oliver E. Craig, Sophy Charlton, Kate Britton, Alison Sheridan, Annie Bones, Helen M. Talbot, Rebecca Macdonald, Michael P. Richards

Bibliographic record

VenueArchaeometry · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsSimon Fraser University
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaUniversity of AberdeenUK Research and Innovation
KeywordsMesolithicArchaeologyIsotopeGeologyGeographyNuclear physicsPhysics

Abstract

fetched live from OpenAlex

Abstract Numerous isotopic studies of Scottish Mesolithic and Neolithic diets suggest a shift from marine‐based to terrestrial‐based subsistence strategies. However, bulk collagen isotope analysis may overlook low‐level marine food consumption. This study combines bulk collagen stable isotope data from four Neolithic sites (Quanterness, Rattar East, Ness of Brodgar, and Knap of Howar) with nitrogen compound‐specific isotope analysis (CSIA‐AA) from one Late Mesolithic and five Neolithic sites. CSIA‐AA, applied here for the first time to Scottish material, reveals limited but detectable aquatic resource use by some Neolithic individuals in Orkney. These findings highlight the complexities in identifying marine contributions to diet and underscore the value of CSIA‐AA in distinguishing direct marine consumption from other sources of elevated nitrogen isotope values, such as seaweed or animals with marine‐influenced diets.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.217
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 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

Citations5
Published2025
Admission routes2
Has abstractyes

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