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Record W7011762696

Writ in Barracks

2023· article· en· W7011762696 on OpenAlexaboutno aff

Bibliographic record

VenueVědecká knihovna v Olomouci (Research Library in Olomouc) · 2023
Typearticle
Languageen
FieldChemistry
TopicHistory and advancements in chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsWritPoetryNewspaperQuarter (Canadian coin)ColonialismFirst world warPublishing
DOInot available

Abstract

fetched live from OpenAlex

One of Wallace’s first published works, ‘Writ in Barracks’ is a collection of poems written while the author was stationed in South Africa and acting as a reporter. While there is a sense of ‘king and country’ that pervades the work, what sets this book apart from others is the contrast of outward bravado against inner fear. Honest, searing, and occasionally funny, these poems offer an incisive insight into life behind the lines, during what came to be known as the Second Boer War. ‘Writ in Barracks’ is the perfect poetry collection for those interested in colonial history. Born in London, Edgar Wallace (1875 1932) was an English writer so prolific that his publisher claimed that he was responsible for a quarter of all books sold in England. Leaving school at the age of 12, Wallace made his first steps into the literary world by selling newspapers on the corner of Fleet Street. He worked as a war correspondent after joining the army at age 21, which honed his writing abilities. This led to the creation of his first book ‘The Four Just Men.’ Wallace is best remembered as the co-creator of ‘King Kong,’ which has been adapted for film 12 times (most notably directed by ‘Lord of the Rings’ director, Peter Jackson, and starring Jack Black and Naomi Watts). However, he leaves behind an extensive body of work, including stories such as ‘The Crimson Circle’ and ‘The Flying Squad’.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.146
Threshold uncertainty score0.489

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0230.002
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.1460.020

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 head0.088
GPT teacher head0.375
Teacher spread0.287 · 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
Published2023
Admission routes1
Has abstractyes

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