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Record W2976496046 · doi:10.3406/paleo.2018.5785

Jawafat Shaban and the Late Neolithic in Wâdî al-Bîr, Northern Jordan

2018· article· fr· W2976496046 on OpenAlexaboutno aff
Edward B. Banning, Khaled Abu Jayyab, Philip Hitchings, Isaac Ullah, Stephen Rhodes, Emma Yasui, Elizabeth Gibbon, Natalia Maria Handziuk, Arno Glasser

Bibliographic record

VenuePaléorient · 2018
Typearticle
Languagefr
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
Fundersnot available
KeywordsWadiHumanitiesGeographyArchaeologyArt

Abstract

fetched live from OpenAlex

Au cours du mois d’août 2014, une équipe de l’université de Toronto a effectué des sondages en trois points du bassin de Wadi Quseiba, à l’ouest d’Irbid, en Jordanie. L’un d’eux était un «site candidat » mis au jour lors de la prospection du Wadi Quseiba à Wadi al-Bir, l’un des principaux affluents de Wadi Quseiba, au cours de la saison 2013. Il révéla des traces certaines d’occupation pendant le Néolithique récent (ou Chalcolithique ancien), qui comprennent de la poterie et de l’outillage lithique en grand nombre, et du mobilier en pierre, ainsi que des couches associées, des fosses et des traces d’architecture. Les découvertes suggèrent une datation dans la seconde moitié du 6e millénaire avant J.-C., contemporaine de Tabaqat al-Bûma à Wadi Ziqlab, au sud, et des sites dans le Nord d’Israël, que les archéologues attribuent à la « culture Wadi Rabah » . Ce site, conjointement avec les nouvelles méthodes utilisées pour le découvrir, a des répercussions plus larges pour notre compréhension de l’étendue de l’occupation néolithique dans le Sud du Levant au cours du 6e millénaire avant J.-C. et la nature des paysages sociaux du Néolithique.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.195
Teacher spread0.186 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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