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Record W2916808886 · doi:10.30549/opathrom-06-10

The Swedish Jordan Expedition 2011 and 2012 at Tall Abu al-Kharaz

2013· article· en· W2916808886 on OpenAlexaboutno aff
Peter M. Fischer, Teresa Bürge, D.M. Blattner, Mohammad Alrousan, A. Abu Dalo

Bibliographic record

VenueOpuscula Annual of the Swedish Institutes at Athens and Rome · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsnot available
FundersKungl. Vitterhets Historie och Antikvitets Akademien
KeywordsContext (archaeology)Quarter (Canadian coin)ArchaeologyIron AgeAncient historyPeriod (music)GeographyExcavationAbandonment (legal)Style (visual arts)HistoryHuman settlementSettlement (finance)ArtLaw

Abstract

fetched live from OpenAlex

Tall Abu al-Kharaz, a twelve hectare-large tell in the central Jordan Valley, was occupied for approximately five millennia. In earlier excavation seasons most of the early Iron Age remains were found to have been disturbed by later settlers. Between 2009 and 2012 excavations revealed an extremely well-preserved city quarter dating from around 1100 BC, which represents an essential part of the settlement history of this city. The stone-built architectural compound consists of 21 rooms, with walls still standing to a height of more than 2 m. The inventories of these rooms, which comprised more than 200 complete vessels and other objects, were remarkably intact. Amongst the finds were imports from Egypt and Phoenicia. There were also finds which are associated with the culture of the Sea Peoples/Philistines, such as several Aegean and Cypriote-style vessels and other objects. The find context points to a hasty abandonment of the city. In the past, the beginning of the Iron Age has often been referred to as “the Dark Ages”, a period of cultural regression: this categorization is not appropriate to the find situation at Tall Abu al-Kharaz where the remains of a wealthy society, with far-reaching intercultural connections, can be identified.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score1.000

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 studies0.0030.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.200
Teacher spread0.188 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2013
Admission routes1
Has abstractyes

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