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Record W3046509678 · doi:10.5539/ass.v16n8p102

Some New Epigraphy Material from the Hashemite Kingdom of the Jordan

2020· article· en· W3046509678 on OpenAlexvenueno aff
Ali Al‐Manaser, Hind Mohammad Turki Al Turki

Bibliographic record

VenueAsian Social Science · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsnot available
FundersUniversity of Oxford
KeywordsEpigraphyRelation (database)Interpretation (philosophy)Meaning (existential)KingdomHistoryVerbArchaeologyAncient historyLinguisticsComputer sciencePhilosophyEpistemology

Abstract

fetched live from OpenAlex

The aim of this research is to present a new collection of ANA inscriptions (Safaitic) discovered in 2017 in the Jordanian northeastern Badia in the area of Tall Al-Hafit. The research attempts to add a new meaning to the interpretation of the verb ʿwr in the Safaitic inscriptions. This research also introduces a new inscription bearing a reference to the town of Salkhad, which is located in southern Syria. This is the fifth inscription mentioning the name of this town. In addition, the research attempts to shed light on the importance of interpreting Safaitic inscriptions in relation to their geographical locations (the places where the inscriptions were discovered). This is because it is believed that these inscriptions and the meanings their authors wanted to convey can be better understood when interpreting these inscriptions in relation to their geographical contexts.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0040.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.002

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 head0.038
GPT teacher head0.232
Teacher spread0.194 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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