MétaCan
Menu
Back to cohort

Spanish Validation of the Syndrom Kurztest (SKT)

2001· article· en· W2330999541 on OpenAlexaff
Luis Fornazzari, Francisco Cumsille, Fernando Quevedo, Pilar Martínez Quiroga, Pedro Rioseco, G. Klaasen, Carmelo Gómez Martínez, G. Rhode, Claudio Sacks, E. Rivera, I. Gassic, F. Hammersley, A Hoppe, Pablo Arriagada, R. Flaskamp

Bibliographic record

VenueAlzheimer Disease & Associated Disorders · 2001
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
FundersNational Institute on Aging
KeywordsFunctional illiteracyMultinational corporationNeuropsychologyTest (biology)PsychologyNeuropsychological testPopulationEtiologyClinical psychologyMedicineGerontologyPsychiatryCognitionEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

There is an urgent need in multinational studies for efficient and sensitive tests for the evaluation of dementias. These tests are used to investigate the regional characteristics of dementias, providing possible insight into the different etiologies of the disorders. These tests are also utilized to assess the outcome of treatment interventions at multinational levels. We validated and standardized the Syndrom Kurztest, a brief European neuropsychological test, in a population of elderly Chileans, possessing high levels of illiteracy. In our sample, the SKT was found to be an effective instrument for the diagnosis of dementias, and for differentiating mild-moderate from severe degrees of the disease. There was a good correlation between the scores on the SKT and the age of the participants, but the gender and the years of schooling had no effect. The test is a useful contribution to the study of dementias, found in the aging developing world, particularly because it can be used in illiterate populations.

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)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.017
GPT teacher head0.284
Teacher spread0.268 · 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 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

Citations20
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueAlzheimer Disease & Associated DisordersSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207