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Record W2277720584 · doi:10.1590/2317-1782/20152015029

Bateria Montreal de Avaliação da Comunicação - versão portuguesa: efeito da idade e escolaridade

2015· article· pt· W2277720584 on OpenAlexaffabout
Mônica de Souza Kerr, Karina Carlesso Pagliarin, Ana Mineiro, Perrine Ferré, Yves Joanette, Róchele Paz Fonseca

Bibliographic record

VenueCoDAS · 2015
Typearticle
Languagept
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversité de Montréal
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsPortugueseEuropean PortuguesePsychologyBonferroni correctionAge groupsFormal educationAnalysis of varianceHumanitiesDevelopmental psychologyDemographyAudiologyMedicineSociologyArtLinguisticsPedagogyStatisticsMathematicsPhilosophy

Abstract

fetched live from OpenAlex

PURPOSE: To verify age and education effects on communication performance of healthy adults in the Montreal Communication Evaluation Battery, Portuguese version (MAC-PT). METHODS: The sample comprised 90 healthy adults from Portugal, European Portuguese speakers, divided into nine groups according to educational level (4-9, 10-13, and > 13 years of formal schooling) and age (19-40, 41-64, and 65-80 years). The influence of age and education was assessed by comparing mean scores between groups, using a two-way analysis of variance followed by Bonferroni post hoc tests (p ≤ 0.05). RESULTS: The results showed that participants' performance was influenced by age in pragmatic-inferential, discursive, and prosodic tasks. Education had the greatest influence on the performance in all processes evaluated by the MAC-PT. CONCLUSION: Age and education seem to influence the communicative performance and should be considered in the assessment of neurological patients.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.101
GPT teacher head0.333
Teacher spread0.232 · 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 designBench or experimental
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
Published2015
Admission routes2
Has abstractyes

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