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Record W2141609105 · doi:10.1016/j.jalz.2005.06.227

[P‐166]: Preservation of episodic and semantic musical memory in severe Alzheimer's disease

2005· article· en· W2141609105 on OpenAlexaff
Luis Fornazzari, Tonya Castle, Shailesh Nadkarni, Dielle Miranda, Nina Apanasiewicz, Marilyn Ambrose, F. Ruth Phillips

Bibliographic record

VenueAlzheimer s & Dementia · 2005
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEpisodic memorySemantic memoryPsychologyCognitive psychologyReconstructive memoryAutobiographical memoryCognitionRecallMusicalExplicit memoryNeuroscience

Abstract

fetched live from OpenAlex

The neural networks activated during music perception and interpretation are morphologically and functionally different from other cognitive funtions. Particularly verbal and visuospatial episodic and semantic memory have different modular networks in relation to episodic and semantic musical memory. To compare both memory system in a professional musician, piano player with Alzheimer's disease. We compared her capacity for learning and remembering verbal and written material versus auditory and visual musical memory material during 7 consecutive days. After the 4th days she was able to learn and recall new auditory music, improving by day in rhythm, melody and performance. Her mood, using Geriatric Depression Scale, and behavioral difficulties, using NPI, also showed improvement. However she showed no learning and or memory for the verbal, written or the visual musical material. The exploration of semantic and episodic musical memory in AD and related dementias may be a way to evaluate cognitive functions when other are not possible.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0040.001

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 head0.045
GPT teacher head0.323
Teacher spread0.278 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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