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Record W3135333176 · doi:10.1080/23273798.2021.1896012

Cognitive Reserve and language processing demand in healthy older adults

2021· article· en· W3135333176 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.

Bibliographic record

VenueLanguage Cognition and Neuroscience · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsCognitionResearch centrePsychologyGerontologyCognitive impairmentArtMedicineLibrary sciencePsychiatryComputer science

Abstract

fetched live from OpenAlex

Cognitive Reserve (CR) refers to cognitive resources acquired through experiences along the lifespan that allow for flexibility in coping with neurocognitive changes. Investigating the role of CR measures across well-established psycholinguistic features can provide new insight into how CR interplays with cognition. Sixty-five Italian older adults performed a Lexical Decision, a Semantic Matching and a Sentence Reading task. We observed the effects of CR on reaction times and accuracy while varying lexical frequency (high vs low) and lexical semantics (concrete vs abstract) and on reading times of sentences with either syntactic or semantic violations. In the Lexical Decision and Semantic Matching tasks, CR played a role in processing low frequency and abstract words. In the Sentence Reading Task, CR influenced reading times, particularly in the presence of syntactic violations. CR predicts cognitive performance in tasks that require language demands at different levels.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.326
Teacher spread0.297 · 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