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Record W2462091879 · doi:10.3138/ecf.27.1.151

Book Reviews/Critiques de livres

2014· article· en· W2462091879 on OpenAlexvenueno aff

Bibliographic record

VenueEighteenth-Century Fiction · 2014
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsnot available
Fundersnot available
KeywordsCalaisHistoryPoliticsBiographyPoetryArt historyClassicsArtLiteratureLaw

Abstract

fetched live from OpenAlex

April London, The Cambridge Introduction to the Eighteenth-Century Novel, reviewed by Megan A. Woodworth ed. Michael Bell, The Cambridge Companion to European Novelists, reviewed by Megan A. Woodworth ed. John Richetti, The Cambridge History of English Literature, 1660–1780, reviewed by Megan A. Woodworth Steven Moore, The Novel: An Alternative History, 1600–1800, reviewed by Megan A. Woodworth ed. Elizabeth C. Mansfield and Kelly Malone, Seeing Satire in the Eighteenth Century, SVEC 2013:02, reviewed by Geoffrey Sill Ashley Marshall, The Practice of Satire in England 1658–1770, reviewed by Geoffrey Sill Kelly McGuire, Dying to Be English: Suicide Narratives and National Identity, 1721–1814, reviewed by Nicole Reynolds Wolfram Schmidgen, Exquisite Mixture: The Virtues of Impurity in Early Modern England, reviewed by Katherine M. Quinsey Megan A. Woodworth, Eighteenth-Century Women Writers and the Gentlemen’s Liberation Movement: Independence, War, Masculinity, and the Novel, 1778–1818, reviewed by Robert W. Jones Andrew Swift and Kirsten Elliott, Literary Walks in Bath: Eleven Excursions in the Company of Eminent Authors, reviewed by John Eglin Philippe Barr, Rétif de La Bretonne spectateur nocturne: Une esthétique de la pauvreté, reviewed by Françoise Le Borgne Kathryn R. King, A Political Biography of Eliza Haywood, reviewed by Juliette Merritt Eugenia Zuroski Jenkins, A Taste for China: English Subjectivity and the Prehistory of Orientalism, reviewed by Chi-ming Yang

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)0.002
metaresearch head score (Gemma)0.007
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: Review · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score0.370

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.006
Science and technology studies0.0040.004
Scholarly communication0.0110.005
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1110.064

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 head0.296
Teacher spread0.280 · 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
GenreReview

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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