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Record W4320020229 · doi:10.24852/pa2022.4.42.185.193

On the Way to the Crimea and from the Crimea. Or-Kapu (Perekop): introduction to the historical topography of the Crimean Khanate town

2022· article· en· W4320020229 on OpenAlexaboutno aff
Bocharov Sergei G.

Bibliographic record

VenuePovolzhskaya Arkheologiya (The Volga River Region Archaeology) · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicAncient Mediterranean Archaeology and History
Canadian institutionsnot available
Fundersnot available
KeywordsFortress (chess)ArchaeologyQuarter (Canadian coin)Settlement (finance)Ancient historyPlan (archaeology)State (computer science)GeographyHistory

Abstract

fetched live from OpenAlex

The article reveals the main points of the historical topography of the Crimean Khanate town – Or-Kapu, and most importantly, proposed a graphic reconstruction of its general plan for the third quarter of the 18th century, the final stage of the existence of this state. The reconstruction of the historical topography of the late medieval town is based on three main categories of sources – written, cartographic and archaeological. All basic elements of the historical topography of the late medieval town and building inside the stone fortress are recreated by the author. The plan of town’s quarters and streets was reconstructed. Three town mosques, a bath-house, eight wells that supplied people with water, one hotel – a caravanserai, rows of stalls, and a cemetery were localized. It has been possible to determine that it was the smallest settlement in the state. By the final stage of the existence of the Crimean Khanate, the urban area of Or-Kapu was about 19.3 hectares, the town cemetery was about 5.0 hectares.

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: none
Teacher disagreement score0.018
Threshold uncertainty score0.037

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 studies0.0030.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.042
GPT teacher head0.213
Teacher spread0.171 · 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
Published2022
Admission routes1
Has abstractyes

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