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Record W2082283109 · doi:10.1177/0734282908323628

Cognitive Differences for Ages 16 to 89 Years (Canadian WAIS-III)

2008· article· en· W2082283109 on OpenAlexaffabout
Hoyee Flora Lee, Richard L. Gorsuch, Donald H. Saklofske, Colleen A. Patterson

Bibliographic record

VenueJournal of Psychoeducational Assessment · 2008
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyWechsler Adult Intelligence ScaleNormativeDevelopmental psychologyCognitionWorking memoryComprehensionPerceptionWechsler Preschool and Primary Scale of IntelligenceYoung adultWechsler Intelligence Scale for ChildrenAudiologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Adult cognitive age differences in the Wechsler Adult Intelligence Scale—III Canadian normative data were curvilinear for most scales and for the Verbal Comprehension (VC), Perceptual Organization (PO), and Working Memory (WM) factors. These showed stable or increasing scores in early adulthood followed by decreasing scores, necessitating a nonlinear (continuous parameter estimation) approach to modeling adult age differences. Means were as high as or higher than the 18-year-olds until 60 years for PO and 70 years for WM and VC. As the means showed no interpretable differences across 20 to 30 years of adult cohorts, no one year can be identified as the highest scoring. “What If” analyses correcting for possible Flynn effects and for the hypothesis that changes in Processing Speed may underlie some of the age differences suggest that further testing of these two effects is a necessary prerequisite to advancing our understanding of adult age differences.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.101
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.092
GPT teacher head0.421
Teacher spread0.329 · 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

Citations15
Published2008
Admission routes2
Has abstractyes

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