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Record W2502178899 · doi:10.1017/cbo9780511835254.005

‘He held to the last quarter hour’

2011· book-chapter· en· W2502178899 on OpenAlexaboutno aff
Elizabeth Greenhalgh

Bibliographic record

VenueCambridge University Press eBooks · 2011
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)HistoryArchaeology

Abstract

fetched live from OpenAlex

While Foch had been carrying out his role as commander of XX Corps within Second Army by holding down as many German forces as possible on the eastern frontier, the main battles of August 1914, known collectively as the Battles of the Frontiers, had taken place. By using First and Second Armies in Alsace and Lorraine, Joffre had retained the flexibility to deploy France’s Third and Fourth Armies in the centre and Fifth Army on the left of the line. Joffre knew that German troops were marching through Luxembourg and Belgium, but he did not know their strength or their exact route. As it became clear that the German right wing was stronger than had first been estimated, Joffre drew the conclusion that therefore the centre must have been weakened. First and Second Armies had fulfilled their roles of holding enemy forces admirably, and so, if the German right was indeed stronger, then the forces deployed in front of Third and Fourth Armies in the centre must be weaker. As a consequence, Joffre sent these two armies into Belgium on 21 August (the day after Rupprecht’s attack at Morhange) with orders to attack the enemy wherever he was found. Although Fourth Army was six-corps strong, the opposing German forces were stronger still. Joffre had miscalculated disastrously and the costly Battles of the Frontiers were the result.

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)0.003
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: Other
Teacher disagreement score0.131
Threshold uncertainty score0.438

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1310.056

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 head0.025
GPT teacher head0.214
Teacher spread0.189 · 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
Published2011
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicWorld Wars: History, Literature, and ImpactFrench-language works237,207