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Record W4385268093 · doi:10.1044/2023_ajslp-22-00177

Amyotrophic Lateral Sclerosis–Bulbar Dysfunction Index–Remote: Test–Retest and Interrater Reliability of Candidate Items

2023· article· en· W4385268093 on OpenAlexaff
Liziane Bouvier, Jordan R. Green, Carolina Barnett Tapia, Victoria Tilton-Bolowsky, Marc F. Maffei, Zuzana Fless, Katie Seaver, Anna Huynh, Sarah E. Gutz, Rosemary Martino, Agessandro Abrahão, James D. Berry, Lorne Zinman, Yana Yunusova

Bibliographic record

VenueAmerican Journal of Speech-Language Pathology · 2023
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsHealth Sciences CentrePublic Health OntarioSunnybrook Health Science CentreToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsInter-rater reliabilityAmyotrophic lateral sclerosisAudiologyKappaPsychologyReliability (semiconductor)Cohen's kappaPhysical medicine and rehabilitationMedicineDiseaseComputer scienceDevelopmental psychologyPathologyRating scale

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.021
metaresearch head score (Gemma)0.033
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.342
Teacher spread0.322 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Speech-Language Pathology→Same topicDysphagia Assessment and Management→French-language works237,207→