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Record W4387241899 · doi:10.1093/arclin/acad077

Normative Data for the Judgment of Line Orientation Test (Long and Short Forms) in the Quebec-French Population Aged between 50 and 89 Years

2023· article· en· W4387241899 on OpenAlexafffundabout
Carol Hudon, Sylvie Belleville, Florence Belzile, M. Landry, Hannah Mulet‐Perreault, Corinne Trudel, Joël Macoir

Bibliographic record

VenueArchives of Clinical Neuropsychology · 2023
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsUniversité de MontréalUniversité LavalInstitut Universitaire de Gériatrie de MontréalThe Quebec Population Health Research Network
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNormativeTest (biology)PsychologyOrientation (vector space)PopulationLine (geometry)Developmental psychologyDemographySociologyPolitical scienceMathematicsGeometryLaw

Abstract

fetched live from OpenAlex

The Judgment of Line Orientation (JLO) Test of Benton assesses visuospatial processing without requiring motor skills. The test is frequently used in geriatric or brain-injured populations. As with other cognitive tests, performance on the JLO test may vary according to age, level of education, sex, and cultural background of individuals. The present study aimed to establish normative data for a short (15 items) and a long (30 items) form of the JLO. The sample for the short and long forms comprised 198 and 260 individuals, respectively, aged 50-89 years. All participants were French-speaking people from the province of Quebec, Canada. Using regression-based norming, the effects of age, years of formal education, and sex on JLO performance were estimated. The normative adjustment of the JLO short and long forms considered the weight of each predictor on test performance. Results indicated that JLO performance was positively associated with years of formal education and male sex, whereas it was negatively associated with age. Accordingly, normative data were generated using Z-scores and adjusted scaled scores derived from the regression equations. To conclude, the present norms will ease the detection of visuospatial impairment in French-Quebec middle-aged and older adults.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.144
GPT teacher head0.466
Teacher spread0.322 · 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.

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

Citations5
Published2023
Admission routes3
Has abstractyes

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