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Record W2009664805 · doi:10.1177/001458580503900210

CENNI SULLA FRASE IPOTETICA IN DUE DIALETTI DELL' ALTO MOLISE

2005· article· it· W2009664805 on OpenAlexaff
Roberta Iannacito-Provenzano

Bibliographic record

VenueForum Italicum A Journal of Italian Studies · 2005
Typearticle
Languageit
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsLaurentian University
Fundersnot available
KeywordsHumanitiesArtCartographyGeography

Abstract

fetched live from OpenAlex

Quest'articolo consiste nel fornire un quadro descrittivo delle diverse configurazioni del periodo ipotetico in alcuni dialetti molisani della zona isernina. I dialetti rappresentativi in esame appartengono a Villa San Michelle (frazione del comune di Vastogirardi) e a Forli del Sannio, due località nella zona isernina. Si mira a colmare le lacune in questo campo presentando i vari costrutti riscontrati prima di tutto in una serie di registrazioni basate sulla ricerca sul campo a Villa San Michele e, in secondo luogo, esaminando le frasi ipotetiche, che dovrebbero essere riflessioni autentiche del parlato, incluse in alcune commedie scritte dal noto commediografo, pittore, poeta e maestro Antonio Angelone (1933) nel dialetto forlivese. In primo luogo vengono trattate le frasi ipotetiche della realtà che comunque non presentano straordinarie varianti a confronto con il generale assetto linguistico delle zone contigue. In seguito si indaga in maniera approfondita sulla frase ipotetica dell'irrealtà nei dialetti in esame e si presentano dieci configurazioni diverse per questo tipo. Per quanto riguarda il periodo ipotetico dell'irrealtà nel passato vengono esaminate in modo dettagliato anche le varie combinazioni con l'imperfetto dell'indicativo, caratteristica normale in questa zona.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.006
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.020
GPT teacher head0.292
Teacher spread0.272 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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