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Record W4383745138 · doi:10.5325/victinstj.33.1.0258

Christa Zorn. <i>Vernon Lee: Aesthetics, History, and the Victorian Female Intellectual</i>

2005· article· en· W4383745138 on OpenAlexaffabout
Dennis Denisoff

Bibliographic record

VenueVictorians Institute Journal · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIconCitationArt historyState (computer science)DownloadArtLibrary scienceHistoryComputer scienceWorld Wide WebAlgorithm

Abstract

fetched live from OpenAlex

Book Review| December 01 2005 Christa Zorn. Vernon Lee: Aesthetics, History, and the Victorian Female Intellectual Christa Zorn. Vernon Lee: Aesthetics, History, and the Victorian Female Intellectual. Athens: Ohio University Press. 2003. xxxi+213 pp. $49.95. Dennis Denisoff Dennis Denisoff Ryerson University Search for other works by this author on: This Site Google Victorians Institute Journal (2005) 33: 258–261. https://doi.org/10.5325/victinstj.33.1.0258 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation Dennis Denisoff; Christa Zorn. Vernon Lee: Aesthetics, History, and the Victorian Female Intellectual. Victorians Institute Journal 1 December 2005; 33 258–261. doi: https://doi.org/10.5325/victinstj.33.1.0258 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectivePenn State University PressVictorians Institute Journal Search Advanced Search The text of this article is only available as a PDF. Copyright © 2005 by The Pennsylvania State University2005The Pennsylvania State University Article PDF first page preview Close Modal You do not currently have access to this content.

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)0.002
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: Review
Teacher disagreement score0.085
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0850.027

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 head0.209
Teacher spread0.185 · 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
Published2005
Admission routes2
Has abstractyes

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