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Record W7125408741 · doi:10.3989/tp.2025.1064

On the fringes of Atlantic Rock Art: A multidisciplinary approach to El Riscal (Seville, Spain)

2025· article· en· W7125408741 on OpenAlexfundno aff
Miguel Ángel Rogerio Candelera, Alba Fuentes Porto, Timoteo Rivera Jiménez, Jordi Ibáñez Insa, José Antonio Lozano Rodríguez, A. César González García, Raquel Montero Artús, Leonardo García Sanjuán

Bibliographic record

VenueTrabajos de Prehistoria · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeological and Geological Studies
Canadian institutionsnot available
FundersJunta de AndalucíaRio TintoXunta de Galicia
KeywordsRock artPrehistoryProspectionMultidisciplinary approachRock shelterTemporalityPhotogrammetry

Abstract

fetched live from OpenAlex

This paper presents multi-disciplinary research undertaken between 2022 and 2024 at El Riscal, the only rock art station known in Seville (Andalusia, Spain), a territory otherwise very rich in Late Prehistoric archaeological remains. Discovered in the 1980s and first published in the early 1990s, El Riscal presents engraved motifs not documented in other parts of southern Spain, where schematic-style painted rock art is prevalent. The set of methods employed in this research includes petrology, chemical characterisation (XRD, SEM-EDS), digital photogrammetry and digital image analysis, archaeological prospection and archaeoastronomy. The results throw new light on the characteristics and temporality of the site, with a pervasive significance through time. This, in turn, invites a new approach to the geographical distribution of the various traditions and styles present in Iberian rock art. This research also suggests that re-examining previously published rock art sites could lead to a better understanding of styles, chronologies and traditions.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.242
Teacher spread0.211 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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