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Record W4388993317

The Natufian’ hamlet of Eynan-Mallaha - Report Season 2022

2023· preprint· en· W4388993317 on OpenAlexaff
Fanny Bocquentin, Lior Weissbrod, Marie Anton, Camille de Becdelièvre, Laurent Davin, Laure Dubreuil, Niels Fourchet, David E. Friesem, Brent Whitford

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2023
Typepreprint
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsTrent University
Fundersnot available
KeywordsHAMLET (protein complex)ArchaeologyGeographyArtLiterature
DOInot available

Abstract

fetched live from OpenAlex

The discovery of the site of Eynan-Mallaha (EM) (figure 1) first led to the realization that Natufian foragers had transitioned to a mostly settled way of life. The site’s rich and eco-diverse environmental context within the Jordan rift valley appears to have been exploited by sedentary hunter-gatherer groups over the lengthy period between 12500 and 9500 calibrated BCE. The past 22 excavation seasons conducted at the site have greatly contributed to the consolidation of Franco-Israeli collaboration in archaeology and the training of young researchers from both countries. Optimal conditions for a resumption of the excavations at Eynan-Mallaha have now coalesced: (1) the near completion of a monograph on the most recent campaign (1996–2005) directed by F. Valla and H. Khalaily focused on the Final Natufian; and (2) the ongoing work on the archives of J. Perrot for a better highlighting and dissemination of the discoveries made on the Late and Early Natufian between 1955 and 1976. The methods of high-precision excavation and data acquisition and analysis were applied in a first exploratory season (June–July 2022), with the support of the IAA, the CNRS and generous Foundation ARPAMED and Irene Levi Sala CARE, yielding highly promising results that more than justify launching our plans for a long term project.

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)0.001
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 score0.044
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0440.006

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 head0.029
GPT teacher head0.235
Teacher spread0.205 · 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
Published2023
Admission routes1
Has abstractyes

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