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Record W3162709440 · doi:10.1080/13554794.2021.1924208

“More than words” – Longitudinal linguistic changes in the works of a writer diagnosed with semantic dementia

2021· article· en· W3162709440 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

VenueNeurocase · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersNational Health and Medical Research Council
KeywordsAdverbSemantic dementiaNarrativeLinguisticsPsychologyQuality (philosophy)Computer scienceNatural language processingDementiaArtificial intelligenceCognitive psychologyMedicinePhilosophyFrontotemporal dementiaDisease

Abstract

fetched live from OpenAlex

Leveraging recent advances in automated language analysis and anovel statistical approach utilizing an independent control group, we explored changes in lexical output across two published works of a man diagnosed with semantic dementia. We found significant increase in adverb usage and decline in familiarity, meaningfulness, age of acquisition and co-occurrence probability over 2 years. Collectively, these indices suggest that WR's narrative structure became progressively simpler, lexically less sophisticated, and that words commonly associated together no longer appeared in close proximity. Our study illustrates how degeneration of the semantic knowledge base impacts the production, content, and quality of literary works.

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)0.001
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 score0.330
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.033
GPT teacher head0.287
Teacher spread0.254 · 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