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Record W3146797557

The battle near Durnkrut in 1278: the Alliance between Lev Danilovich and Premysl Ottokar II

2016· article· en· W3146797557 on OpenAlexaboutno aff
Illya Parshyn

Bibliographic record

VenueRossica Antiqua · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval European History and Architecture
Canadian institutionsnot available
Fundersnot available
KeywordsBattleDiplomacyAllianceAncient historyQuarter (Canadian coin)HistoryClassicsPolitical scienceLawArchaeologyPolitics
DOInot available

Abstract

fetched live from OpenAlex

This article presents the analysis of latin sources of XV century. All these chronicles mention that Lev Danilovich, called as “rex Rusciae”, took part in the great battle near Durnkrut in 1278 between Ottokar II of Bohemiaand Rudolf I Habsburg, the founder of Habsburg’s dynasty. All investigated sources indicate Lev Danilovich to be in the troops of Bohemian king. These testimonies are very important to understanding of diplomacy of Galician duke in the last quarter of XIII century. Further scientific debate with involving new sources will shed more light onthis important issue.

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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.005
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.001
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 head0.022
GPT teacher head0.215
Teacher spread0.194 · 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
Published2016
Admission routes1
Has abstractyes

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