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Record W2068904490 · doi:10.1055/s-2006-955119

Clinical Implications of Cross-System Interactions

2006· review· en· W2068904490 on OpenAlexaff
David H. McFarland, Pascale Tremblay

Bibliographic record

VenueSeminars in Speech and Language · 2006
Typereview
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMcGill UniversityCentre for Research on Brain Language and MusicUniversité de Montréal
FundersNational Science Council
KeywordsSwallowingNeuroimagingSpeech productionPsychologyIntervention (counseling)NeuroscienceTask (project management)Perspective (graphical)Cognitive psychologyComputer scienceMedicineArtificial intelligenceSpeech recognition

Abstract

fetched live from OpenAlex

In this review, we briefly highlight potential cross-system interactions between swallowing and speech production, using data from recent neuroimaging studies, common clinical impairments, cross-system treatment effects, and developmental considerations as supporting evidence. Our overall hypothesis is that speech and swallowing (and other motor behaviors) are regulated through a shared network of brain regions and other neural processes that are modulated on the basis of specific task demands. We emphasize the clinical utility of viewing speech and swallowing as being closely linked from both a diagnostic and treatment perspective. We stress the importance of continuing research to explore the common and perhaps distinct neural circuitry underlying speech and swallowing and the clinical intervention strategies that attempt to capitalize on potential cross-system therapeutic benefits.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.001
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 head0.457
Teacher spread0.412 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations68
Published2006
Admission routes1
Has abstractyes

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