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Record W2076185830 · doi:10.1093/arclin/acq013

Normative Data for the Pyramids and Palm Trees Test in the Quebec-French Population

2010· article· en· W2076185830 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArchives of Clinical Neuropsychology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsHôpital Charles-Le MoyneUniversité de SherbrookeUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsNormativeTest (biology)PsychologyPopulationDevelopmental psychologySample (material)Meaning (existential)Boston Naming TestAge of AcquisitionDemographyCognitionSociologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Semantic memory tests assess long-term memory for facts, objects, and concepts as well as words and their meaning. Since it holds culturally shared information, the development of normative data adjusted to the cultural and linguistic reality of the target population is of particular importance. The present study aimed to establish normative data for the Pyramids and Palm Trees Test, a commonly used test of semantic memory, in the French-Quebec population. The normative sample consisted of 214 healthy French-speaking adults and elderly persons from various regions of the province of Quebec. The effects of participants' age, gender, and education level on test performance were assessed. Results indicated that participants' level of education and age, but not sex, were found to be significantly associated with performance on this test. Normative data are presented as means and standard deviations. Overall, the present norms are consistent with those of previous studies with Spanish samples.

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)0.001
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.106
GPT teacher head0.435
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