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Record W4407051724 · doi:10.1016/j.qeh.2025.100058

Lithological and geochemical characterization of ‘adinole’ artefacts from cave deposits in southwest Wales: A material of choice during the late Middle to Upper Palaeolithic

2025· article· en· W4407051724 on OpenAlexaff
R. E. Bevins, Elizabeth A. Walker, Duncan Pirrie, Rob Ixer, I. Saunders, Matthew Power

Bibliographic record

VenueQuaternary Environments and Humans · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsBurnaby Hospital
FundersHigher Education Funding Council for Wales
KeywordsCaveGeologyArchaeologyGeochemistryGeography

Abstract

fetched live from OpenAlex

Twenty-three artefacts previously identified as being manufactured from adinole, a fine-grained metasomatic rock, from late Middle to Upper Palaeolithic cave sites in southwest Wales have been re-examined in terms of their petrology and geochemistry. Standard petrography has been combined with automated SEM-EDS analysis for a single artefact to determine the mineralogy and textures of that artefact, while portable XRF and μXRF have been combined to establish the geochemical characteristics of all twenty-three artefacts analysed. These investigations have shown that the artefacts were manufactured from rhyolite rather than adinole, a misidentification that has been in the literature for over 100 years. Some artefacts appear to cluster on geochemical plots, such as a group of eight artefacts from Hoyle’s Mouth Cave which share petrological characteristics and appear to have come from a common source. In other cases, however, certain artefacts with similar chemistries have dissimilar petrological characteristics and are not from a common source. This highlights the need to consider both petrological and geochemical characteristics when classifying rhyolitic artefacts. The artefacts studied show that this spotted variety of rhyolite was a preferred source of raw material throughout the late Middle and Upper Palaeolithic, despite having no obvious physical or practical advantages. Identifying rhyolite rather than adinole as the raw material used in the manufacture of the studied artefacts negates the need to consider long distance transport of either raw materials or finished artefacts. It strongly suggests that people in southwest Wales, where raw materials were scarce, were using materials that were local to them. Further, there is evidence that people were effectively planning for future use or reuse of artefacts, involving curation of tools. The next phase of work will use the lithological characteristics identified here to explore potential sources for the raw material used in the manufacture of these artefacts.

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 score0.016
Threshold uncertainty score0.252

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 head0.013
GPT teacher head0.215
Teacher spread0.202 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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