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Record W4407063970 · doi:10.1016/j.ara.2025.100600

Natufian architecture 12,000 years ago: Analyzing ‘building stones’ at Nahal Ein Gev II

2025· article· en· W4407063970 on OpenAlexafffund
Laure Dubreuil, Leore Grosman

Bibliographic record

VenueArchaeological Research in Asia · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicAncient Mediterranean Archaeology and History
Canadian institutionsTrent University
FundersSocial Sciences and Humanities Research Council of CanadaIsrael Science Foundation
KeywordsArchitectureGeographyArchaeologyHistoryAncient history

Abstract

fetched live from OpenAlex

In the Southern Levant, the Natufians established a long-lasting tradition of using stones, along with other materials, for construction. Initial field observations at Nahal Ein Gev II suggested that such stones are natural blocks or cobbles that frequently underwent some kind of modification. To further investigate this pattern and better understand construction techniques and design, a protocol was developed at the site to record and analyze the construction stones, labelled BL for ‘Building Stones.’ This paper presents our initial results. Our analysis reveals that basalt and limestone were commonly used as BL, consistent with the lithology of the geological formations around the site. A large proportion of the BL are broken, perhaps as a result of intentional ‘calibration’ of the stones aimed at making them fit into the structure's walls. Consistency in modal BL size reveals some of the norms that underlie the design of the structures. The presence of several types of sheen was noted on the BL; some forms being related to the use of bonding material employed in wall construction, while other forms may indicate surface treatment. Finally, the construction traditions documented at the site are considered in the broader context of Natufian technical innovation and inter-site variability.

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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.080
GPT teacher head0.343
Teacher spread0.264 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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