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Record W4284963965 · doi:10.1121/10.0012186.3

10.1121/10.0012186.3

2022· dataset· en· W4284963965 on OpenAlexfundno aff

Bibliographic record

VenueDefault Digital Object Group · 2022
Typedataset
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Cambridge
KeywordsComputer science

Abstract

fetched live from OpenAlex

Lateral vocalization is a cross-linguistically common phenomenon where a lateral is realized as a glide, such as [w, j], or a vowel [u, i]. In this paper, we focus on the articulatory triggers that could cause lateral vocalization. We examined Brazilian Portuguese, a language known for the process of lateral vocalization in coda position. We examined the lateral in onset and coda position in four vocalic environments and compared the dynamic tongue contours and contours at the point of maximum constriction in each environment. We also performed biomechanical simulations of lateral articulation and the vocalized lateral. The results indicate increased tongue body retraction in coda position, which is accompanied by tongue body raising. Simulations further revealed that vocalized laterals mainly recruit intrinsic lingual muscles along with the styloglossus. Taken together, the data suggest that vocalization is a result of positional phonetic effects including lenition and additional retraction in the coda position.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.502
Threshold uncertainty score0.717

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0060.002
Open science0.0040.004
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.4980.747

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 head0.026
GPT teacher head0.329
Teacher spread0.303 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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