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Record W2955972610 · doi:10.1163/15700577-12341340

An Old Persian Inscription from Phanagoria

2019· article· en· W2955972610 on OpenAlexaboutno aff
В. Д. Кузнецов, Alexander B. Nikitin

Bibliographic record

VenueAncient Civilizations from Scythia to Siberia · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEurasian Exchange Networks
Canadian institutionsnot available
Fundersnot available
KeywordsPersianAncient historyPeninsulaBlack seaContext (archaeology)SteleQuarter (Canadian coin)EmpireArchaeologyHistoryArtPhilosophyGeology

Abstract

fetched live from OpenAlex

Abstract This article is a publication of the fragmentary Old Persian inscription from the ancient Greek city of Phanagoria (the Taman Peninsula, Russia). The inscription was found in a private house built over the ruins of the city’s fortifications, which perished in a fire in the late first or the early second quarter of the 5th century BC. The fragment of the stele bears six partially preserved lines of the text. The signs at the beginning and the end of each line are missing. Due to the fragmentary nature of the inscription, its contents can not be determined. However, the archaeological context of the find allows us to attribute its authorship to King Xerxes. The new document attests that the Persian Empire took an active interest in the northern coast of the Black Sea.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.294
Teacher spread0.278 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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