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Record W2743963768 · doi:10.1017/aaq.2017.37

CENTERED ON THE WETLANDS: INTEGRATING NEW PHYTOLITH EVIDENCE OF PLANT-USE FROM THE 23,000-YEAR-OLD SITE OF OHALO II, ISRAEL

2017· article· en· W2743963768 on OpenAlexaff
Monica N. Ramsey, Arlene M. Rosen, Dani Nadel

Bibliographic record

VenueAmerican Antiquity · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhytolithGeographyWetlandAssemblage (archaeology)Historical ecologyEcologyArchaeologyPaleoethnobotanyAgriculturePollenBiology

Abstract

fetched live from OpenAlex

Epipaleolithic hunter-gatherers are often interpreted as playing an important role in the development of early cereal cultivation and subsequent farming economies in the Levant. This focus has come at the expense of understanding these people as resilient foragers who exploited a range of changing micro habitats through the Last Glacial Maximum. New phytolith data from Ohalo II seek to redress this. Ohalo II has the most comprehensive and important macrobotanical assemblage in Southwest Asia for the entire Epipaleolithic period. Here we present a phytolith investigation of 28 sediment samples to make three key contributions. First, by comparing the phytolith assemblage to a sample of the macrobotanical assemblage, we provide a baseline to help inform the interpretation of phytolith assemblages at other sites in Southwest Asia. Second, we highlight patterns of plant use at the site. We identify the importance of wetland plant resources to hut construction and provide evidence that supports previous work suggesting that grass and cereal processing may have been a largely “indoor” activity. Finally, drawing on ethnographic data from the American Great Basin, we reevaluate the significance of wetland plant resources for Epipaleolithic hunter-gatherers and argue that the wetland-centered lifeway at Ohalo II represents a wider Levantine adaptive strategy.

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 score0.035
Threshold uncertainty score0.956

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.043
GPT teacher head0.252
Teacher spread0.209 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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