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Record W2516096641 · doi:10.1111/1460-6984.12276

Semantic fluency in aphasia: clustering and switching in the course of 1 minute

2016· article· en· W2516096641 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Language & Communication Disorders · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsnot available
FundersWellcome TrustHeart and Stroke Foundation of Canada
KeywordsFluencyVerbal fluency testPsychologyAphasiaCognitive psychologyCluster analysisAudiologyTask (project management)Control (management)Cluster (spacecraft)Word (group theory)Developmental psychologyCognitionLinguisticsComputer scienceNeuropsychologyArtificial intelligenceNeuroscienceMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Verbal fluency tasks are included in a broad range of aphasia assessments. It is well documented that people with aphasia (PWA) produce fewer items in these tasks. Successful performance on verbal fluency relies on the integrity of both linguistic and executive control abilities. It remains unclear if limited output in aphasia is solely due to their lexical retrieval difficulties or has a basis in their executive control abilities. Analysis techniques, such as temporal characteristics of word retrieved, clustering and switching, are better positioned to inform the debate surrounding the lexical and/or executive control contribution for success in verbal fluency. AIMS: To investigate the differences in quantitative (i.e., number of correct words) and qualitative (i.e., switching, clustering and word-retrieval times) performances on animal fluency task as a function of time between PWA and healthy control speakers (CS). METHODS & PROCEDURES: Animal fluency data for 60 s were collected from 34 PWA and 34 CS, and responses were time stamped. The 60-s period was divided into four equal intervals of 15 s each (i.e., 15, 30, 45 and 60 s). The number of correct words, cluster size, number of switches, within-cluster pause and between-cluster pause were evaluated as a function of four 15-s time intervals between PWA and CS. OUTCOMES & RESULTS: Compared with CS, PWA produced fewer words, had smaller cluster sizes and switched a fewer number of times. A decrease in the number of switches correlated with an increase in between-cluster pause durations. PWA showed longer within- and between-cluster pauses than CS. The two groups showed specific differences in the temporal pattern of the responses: as time evolved both PWA and CS showed decreased productivity for the number of correct words, but PWA reached the asymptote earlier in the time course than CS, neither group showed a change in cluster size, and the number of switches decreased as a function of time only for CS. CONCLUSIONS & IMPLICATIONS: The findings suggest that for PWA the search and retrieval process is less productive and more effortful. This is indicated by smaller cluster size, fewer switches associated with increased between-cluster pause durations, as well as overall slowed retrieval times for the words. This shows that the difficulties with verbal fluency performance in aphasia have a strong basis in their lexical retrieval processes, as well as some difficulties in the executive component of the task.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.016
GPT teacher head0.317
Teacher spread0.301 · 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