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Record W2809588103 · doi:10.5539/ijel.v8n5p230

Syllabification of Bi-Consonantal Clusters Between Vowels in Albanian

2018· article· en· W2809588103 on OpenAlexvenueno aff
Artan Xhaferaj

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsnot available
Fundersnot available
KeywordsSyllabificationSyllableSonority hierarchyLinguisticsFocus (optics)Computer scienceSpeech recognitionPhoneticsNatural language processingMathematicsPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Syllabification is one of the most complex issues in Albanian phonetics. An extensive treatment of the topic was made by Dodi (2004), who, thanks to a thorough acquaintance with the existing literature on the area, also clearly states the drawbacks of the main theories of the syllable, based on material from the Albanian language. However, despite the huge research carried out and the important results achieved, the positions of linguists on syllabification remain different. One reason for this is that linguistic literature lacks an established definition of the syllable as a linguistic unit. In the present research on syllabification, we support some of the existing rules by bringing new arguments and making some additions in order to make them more convincing, with a view to improving and simplifying their practical application. We focus on syllable boundary when there are two consonants between vowels, based on the Sonority Sequencing Principle, on the Syllable Contact Law, the Dispersion Principle, and the Maximum Onset Principle.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.379
Teacher spread0.341 · 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 designObservational
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

Citations2
Published2018
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicPhonetics and Phonology ResearchFrench-language works237,207