АЗАК И ЕГО ОКРУГА В ПЕРВЫЕ ДЕСЯТИЛЕТИЯ ИХ СУЩЕСТВОВАНИЯ. ПРОБЛЕМЫ ЗАРОЖДЕНИЯ И РОСТА ЗОЛОТООРДЫНСКИХ ГОРОДОВ
Bibliographic record
Abstract
The article considers the materials obtained during the study of Azaq and his outskirts possibly dating back to the 3rd quarter of the 13th – the 1st quarter of the 14th centuries. The authors distinguish three chronological phases, with each of them characterized on the basis of materials from closed archaeological complexes. At the fi rst stage, in the middle of the 13th century, the growth of Azaq was surpassed by the development of a rural settlement network in the lower reaches of the Don. Some of them were comparable or even greater than Azaq in terms of area at the early stage of development. Most of the settlements emerged as early as in the beginning of the 14th century. The authors conclude that the most rapid growth of the town occurred during the reign of Khan Tokhta. The town developed less rapidly in the initial period of Uzbek’s rule. The structure of urban districts and a street network developed by 1325. In terms of methodology, of great importance is that the development of the city was signifi cantly ahead of the development of monetary circulation, particularly its coin variation. Coins are absent in most of the complexes, or represented by single fi ndings. Even in thoroughly studied Azaq, traces of the fi rst period of existence vanish due to the numerous materials corresponding to the period of Uzbek’s and Janibek’s reign. The growth phase is insuffi ciently documented due to the fact that most of the materials are deposited in the periods of architectural replanning, and intensive deposition of findings in the layer begins with the onset of crisis phenomena.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".