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Record W3113966628 · doi:10.15826/adsv.2020.48.014

Byzantine Imported Underglaze Monograms in Mediaeval Sougdaia

2020· article· en· W3113966628 on OpenAlexaboutno aff
Vadim Maiko

Bibliographic record

VenueАнтичная древность и средние века · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicByzantine Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsByzantine architecturePotteryScholarshipSign (mathematics)ArchaeologyAncient historyQuarter (Canadian coin)PeninsulaHistoryHoardExcavationArtLaw

Abstract

fetched live from OpenAlex

First time in the scholarship, this paper has analysed Byzantine imported monograms from mediaeval Sougdaia, which appeared on glazed vessels of the Elaborate Incised Ware produced in Constantinople or its environs. With the mediation of Genoese traders, a small number of this pottery was delivered to the markets of the cities in the Crimean peninsula, Sougdaia in particular. So far, many-year-long archaeological excavations discovered seven monograms of the kind, which belonged to three widely known Byzantine types. It should be mentioned that, as it has already been stated in the scholarship, the monograms with the name Michael predominate, though the other types are very few in number. Two typologically similar signs more, showing a double cross with diamond-shaped rays, are traditionally interpreted not as monograms but as ornamental elements typical of the war in question. Using the analysis of analogies and similar images, an attempt has been made to analyse and interpret this sign. All the finds under study originate from four archaeological contexts of mediaeval Sougdaia. Three of them possess a reliable dating to the third quarter of the fourteenth century, and the fourth specimen existed from the mid-fourteenth century to 1475.

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)0.001
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0040.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.054
GPT teacher head0.213
Teacher spread0.158 · 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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