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Record W4319151063 · doi:10.5406/2327753x.39.1.30

Value, Virtues, and Vices, Italian Style: Caesar, Dante, Machiavelli, and Garibaldi

2021· article· en· W4319151063 on OpenAlexaboutno aff
Martha I. Pallante

Bibliographic record

VenueItalian Americana · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicRenaissance and Early Modern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIconStyle (visual arts)CitationValue (mathematics)PublishingTitle pageArtArt historyLibrary scienceLiteratureComputer science

Abstract

fetched live from OpenAlex

Book Review| February 01 2021 Value, Virtues, and Vices, Italian Style: Caesar, Dante, Machiavelli, and Garibaldi Value, Virtues, and Vices, Italian Style: Caesar, Dante, Machiavelli, and Garibaldi by Raymond Angelo Belliotti. Vancouver: Fairleigh Dickinson University Press, 2020. 258pp. Martha I. Pallante Martha I. Pallante Youngstown State University Search for other works by this author on: This Site Google Italian Americana (2021) XXXIX (1): 96–98. https://doi.org/10.5406/2327753X.39.1.30 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Martha I. Pallante; Value, Virtues, and Vices, Italian Style: Caesar, Dante, Machiavelli, and Garibaldi. Italian Americana 1 February 2021; XXXIX (1): 96–98. doi: https://doi.org/10.5406/2327753X.39.1.30 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 CollectiveUniversity of Illinois PressItalian Americana Search Advanced Search The text of this article is only available as a PDF. Copyright 2021 Carla Anne Simonini & Carol Bonomo Albright2021 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)0.003
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: none
Teacher disagreement score0.066
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0660.037

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 head0.015
GPT teacher head0.210
Teacher spread0.196 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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