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Record W98009456 · doi:10.4000/ifha.1087

MINDERMANN, Arend, Urkundenbuch der Bischöfe und des Domkapitels von Verden, Bd. 1 : Von den Anfängen bis 1300 (Verdener Urkundenbuch, 1. Abteilung)

2013· article· de· W98009456 on OpenAlexaff
Nicholas Brousseau

Bibliographic record

VenueRevue de l’Institut français d’histoire en Allemagne · 2013
Typearticle
Languagede
FieldArts and Humanities
TopicHistorical and Archaeological Studies
Canadian institutionsInstitut d'Histoire de l'Amérique Française
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

L’évêché de Verden (Basse-Saxe) situé sur l’Aller, à quelques kilomètres de son confluent avec la Weser, est plus connu des historiens pour le massacre qui s’y tint en 782 lorsque, sur l’ordre de Charlemagne, 4 500 Saxons furent décapités, que pour ses chartes et diplômes. Pourtant, son chartrier n’est pas particulièrement pauvre, ce dont témoigne cette édition. Pour mener à bien son travail, l’éditeur a suivi le plan esquissé par Wilhelm von Hodenberg († 1861) au milieu du XIXe s., qui prév...

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0260.008

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 head0.019
GPT teacher head0.222
Teacher spread0.202 · 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
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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