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Record W2047373179 · doi:10.1044/1058-0360(2005/020)

Speech and Language Findings Associated With Paraneoplastic Cerebellar Degeneration

2005· article· en· W2047373179 on OpenAlexaff
Teresa Paslawski, Joseph R. Duffy, Steven Vernino

Bibliographic record

VenueAmerican Journal of Speech-Language Pathology · 2005
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDysarthriaParaneoplastic cerebellar degenerationMedicineAtaxiaCerebellar DegenerationCerebellar ataxiaEtiologySpasticAudiologySwallowingPathologyPhysical medicine and rehabilitationSurgeryCerebral palsy

Abstract

fetched live from OpenAlex

Paraneoplastic cerebellar degeneration (PCD) is an autoimmune disease that can be associated with cancer of the breast, lung, and ovary. The clinical presentation of PCD commonly includes ataxia, visual disturbances, and dysarthria. The speech disturbances associated with PCD have not been well characterized, despite general acceptance that dysarthria is often part of the initial presentation. A retrospective study was conducted of the speech, language, and swallowing concerns of patients with PCD evaluated at the Mayo Clinic in Rochester, MN, between 1990 and 2001. Prospective speech and language assessments were then conducted with 5 patients who had PCD. While ataxic dysarthria was the most common speech diagnosis, a spastic component was recognized frequently enough to suggest that the subacute (days to weeks) emergence and progression of an ataxic or mixed ataxic-spastic dysarthria in the setting of a more diffuse cerebellar ataxia should raise suspicions about PCD and justify further investigation of a possible immune-related etiology.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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 designCase report
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

Citations5
Published2005
Admission routes1
Has abstractyes

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