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Record W2912767403 · doi:10.1097/wad.0000000000000288

Bilingualism in Primary Progressive Aphasia

2019· article· en· W2912767403 on OpenAlexaff
Ana Sofia Costa, Regina Jokel, Alberto Villarejo‐Galende, Sara Llamas‐Velasco, Kimiko Domoto-Reilley, Jennifer Wojtala, Kathrin Reetz, Álvaro Machado

Bibliographic record

VenueAlzheimer Disease & Associated Disorders · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversity of Toronto
FundersNational Institute on Aging
KeywordsPrimary progressive aphasiaAphasiaPsychologyNeuroscience of multilingualismLanguage impairmentPopulationMedicineCognitive psychologyDementiaDevelopmental psychologyFrontotemporal dementiaPathologyDiseaseNeuroscience

Abstract

fetched live from OpenAlex

BACKGROUND: Primary progressive aphasia (PPA) is a neurodegenerative disorder characterized by progressive deterioration of language. Being rare, reports of PPA in multilingual individuals are scarce, despite more than half of the world population being multilingual. METHODS: We describe clinical characteristics of 33 bilingual patients with PPA, including symptom presentation and language deficits pattern in their first (L1) and second language (L2), through a systematic literature review and new cases retrospectively identified in 5 countries. RESULTS: In total, 14 patients presented with nonfluent/agrammatic variant, 6 with semantic variant, and 13 with logopenic variant, with a median symptom onset of 2 years. Word-finding difficulties was the first symptom in 65% of all cases, initially noticed in L2, and not always the dominant language. Our group had 22 different languages as L1, and 9 as L2. At the whole-group level there was a tendency for parallel impairment in both languages, in line with the shared bilingual neural substrate hypothesis, but each PPA variant showed some heterogeneity. DISCUSSION: Each PPA variant showed heterogeneity, showing the need for comprehensive language and cognitive assessment across languages, as well as further clarification on the role of language mediators.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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 teacher head, not a consensus.

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

Citations23
Published2019
Admission routes1
Has abstractyes

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