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Record W7132534260

Prague Castle and Hradčany in the early modern era. Was extravagance the privilege of the royal court?

2014· article· en· W7132534260 on OpenAlexaboutno aff
G. (Gabriela) Blažková, J. (Josef) Matiášek

Bibliographic record

VenueASEP · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThe RenaissancePrivilege (computing)Quarter (Canadian coin)ExcavationMiddle AgesCzechIdentification (biology)
DOInot available

Abstract

fetched live from OpenAlex

In the almost 90-years' research excavation of Prague Castle and Hradčany (Prague, Czech Republic) a rich collection of find assemblages from early modern (1500-1650) features (market place, cesspits, dumps) has been made. Since the early Middle Ages, Prague Castle has been the centre of the Bohemian state. It was not only the seat of the court and the royal retinue, but as well of the service staff. The bordering quarter of Hradčany was a favoured location of the seats of nobles and clergymen. In a couple of cases, the analysis of iconographic and historical sources has enabled the identification of discrete social environments (craftsmen, imperial staff, nobility, Church). Apart from ceramic finds and Renaissance glass a number of plant macro-remains were helpful in the detailed analysis of individual find assemblages, among them numerous fruit species, medical plants, spices, and tobacco. The correlation between luxury and number of imports on one hand, and social status of their owners on the other, can be thought of on grounds of the long-term survey. At the same time, the find assemblages supplement the research of commercial routes between Prague and other commercial centres, including those oversee.

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 score0.167
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueASEPSame topicHistorical and Cultural Archaeology StudiesFrench-language works237,207