MétaCan
Menu
Back to cohort
Record W2612938157

Análise das habilidades testadas e validade diagnóstica de instrumentos para avaliação de linguagem na doença de Alzheimer, no Brasil

2016· dissertation· en· W2612938157 on OpenAlex
Helen Capeleto Francisco

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicHealth Education and Validation
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Early detection of Alzheimer's disease (AD) can assist in the identification of causes of AD and of interventions that can slow the progression of this disease. The aim of this study was to compare language assessment tools used in Brazil to diagnose AD, to determine: (a) which linguistic skills are assessed, (b) which of these instruments present the greatest diagnostic validity and (b) to identify gaps in the language skills that are evaluated and the availability of research information about the precision and validity of each instrument. To obtain this information, the Bireme database was searched using the keywords language AND Alzheimer AND (test OR assessment OR instrument). Studies were selected using the following criteria: (a) data about the diagnostic validity of language tests for the assessment of AD, (b) conducted in Brazil, (c) published in English or Portuguese, (d) with access to the full text. Seven articles met all these criteria. A second search strategy involved obtaining articles with the information we were seeking, which were cited in the seven articles already selected. An additional six articles were encountered. The instruments analyzed included: Verbal Fluency Test, Teste de Rastreio de Doença de Alzheimer com Provérbios, Token Test, Boston Naming Test, Naming Test of Brief Cognitive Battery The Dog Story, Le Boeuf (1976), Protocole Montréal d'Évaluation de la Communication, Boston Diagnostic Aphasia Examination, Arizona Battery for Communication Disorders of Dementia and ASHA FACS. These instruments were compared with respect to the populations evaluated (elderly with no cognitive impairments, with mild cognitive impairments, and with AD), the number of people tested, their educational levels, and indexes for sensitivity (correct classification of AD patients) and specificity (correct classification of people without cognitive impairments), which reflect the precision and validity of each instrument, with respect to the diagnostic process. Among the language tests that were evaluated, the Semantic Verbal Fluency Test appears to be the test with the best levels of diagnostic validity for detecting cognitive changes during the early stages of AD, in comparison with elderly people with no cognitive impairments (sensitivity of 90.5% and specificity of 80.6% among illiterate elderly; sensitivity of 82.6% and specificity of 100% for the diagnosis of elderly people with more than eight years of education). However, there are many gaps in the information available about the precision and validity of this and all the other instruments, restricting their usefulness in diagnosing AD, at this time.

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.

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)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.349
Teacher spread0.300 · 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