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Record W7111199618 · doi:10.60999/116967

Farinata degli Uberti: revisione delle fonti e nuovi contributi

2024· article· la· W7111199618 on OpenAlexaboutno aff

Bibliographic record

VenueFlorence Research (University of Florence) · 2024
Typearticle
Languagela
FieldSocial Sciences
TopicMedieval and Early Modern Justice
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PoliticsBiographyCharacter (mathematics)

Abstract

fetched live from OpenAlex

Il contributo presenta ed esamina le fonti documentarie, cronachistiche e annalistiche incentrate sulla figura di Manente, detto Farinata, degli Uberti. La loro analisi complessiva delinea gli elementi essenziali della biografia di un personaggio che, alla metà del Duecento, è stato uomo di spicco della sua consorteria, tra i principali capifazione ghibellini e protagonista della politica fiorentina e italiana per circa un quarto di secolo. The contribution presents and examines the documentary, chronicle and annal sources centred on the figure of Manente, known as Farinata, degli Uberti. Their overall analysis outlines the essential elements of the biography of a character who, in the mid-13th century, was a leading man in his consortium, one of the main Ghibelline leaders and a protagonist in Florentine and Italian politics for about a quarter of a century.

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)0.003
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0090.017
Scholarly communication0.0120.006
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.120
GPT teacher head0.373
Teacher spread0.252 · 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
GenreEmpirical

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
Published2024
Admission routes1
Has abstractyes

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