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Record W1798086724 · doi:10.1098/rstb.2014.0357

The development of plant food processing in the Levant: insights from use-wear analysis of Early Epipalaeolithic ground stone tools

2015· article· en· W1798086724 on OpenAlexaff
Laure Dubreuil, Dani Nadel

Bibliographic record

VenuePhilosophical Transactions of the Royal Society B Biological Sciences · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsTrent University
Fundersnot available
KeywordsPaleoethnobotanyStone toolFood processingPleistoceneGeographyArchaeologyBiologyAgricultureFood science

Abstract

fetched live from OpenAlex

In recent years, the study of percussive, pounding and grinding tools has provided new insights into human evolution, more particularly regarding the development of technology enabling the processing and exploitation of plant resources. Some of these studies focus on early evidence for flour production, an activity frequently perceived as an important step in the evolution of plant exploitation. The present paper investigates plant food preparation in mobile hunter-gatherer societies from the Southern Levant. The analysis consists of a use-wear study of 18 tools recovered from Ohalo II, a 23 000-year-old site in Israel showing an exceptional level of preservation. Our sample includes a slab previously interpreted as a lower implement used for producing flour, based on the presence of cereal starch residues. The use-wear data we have obtained provide crucial information about the function of this and other percussive tools at Ohalo II, as well as on investment in tool manufacture, discard strategies and evidence for plant processing in the Late Pleistocene. The use-wear analysis indicates that the production of flour was a sporadic activity at Ohalo II, predating by thousands of years the onset of routine processing of plant foods.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.173
GPT teacher head0.321
Teacher spread0.148 · 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

Citations52
Published2015
Admission routes1
Has abstractyes

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