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Record W4387232195 · doi:10.16899/jcm.1331649

Proverb Comprehension in Primary Progressive Aphasia

2023· article· en· W4387232195 on OpenAlexaboutno aff
İbrahim Can YAŞA, Fenise Selin Karalı

Bibliographic record

VenueJournal of Contemporary Medicine · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsnot available
Fundersnot available
KeywordsPrimary progressive aphasiaComprehensionAphasiaMedicineCognitionCognitive psychologyAudiologyPsychologyLinguisticsFrontotemporal dementiaPathologyPsychiatryDementia

Abstract

fetched live from OpenAlex

Aim: Proverb comprehension was tested in 22 patients with primary progressive aphasia utilizing idiom explanation task. The aim of this study was to determine proverb comprehension in PPA patients using the Proverb Scale. Material and Methods: To assess the participants, Montreal Cognitive Assessment Scale, the Pyramid and Palm Trees test and the Proverb Scale were used. Results: As a result of statistical analysis, there was a significantly difference between svPPA and lvPPA regarding idiom comprehension scores, the Pyramid and Palm Trees Test Scores and MoCA scores. Conclusion: It is an important study to understand how the abstraction in PPA works regarding the language. In PPA subtypes, semantic memory, proverb and MoCA scores were significantly different between logopenic and semantic variants. Although MoCA and proverb comprehension were correlated in svPPA, no correlation was found in lvPPA. With similar studies in the field, it would be possible to better explain the effects of PPA, a disorder characterized by language disorders.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.079
GPT teacher head0.337
Teacher spread0.257 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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