Bibliographic record
Abstract
No AccessPerspectives on Neurophysiology and Neurogenic Speech and Language DisordersArticle1 Dec 2001PROMPT Treatment Method and Apraxia of Speech Arpita Bose and Paula A. Square Arpita Bose University of TorontoToronto, Canada Google Scholar More articles by this author and Paula A. Square University of TorontoToronto, Canada Google Scholar More articles by this author https://doi.org/10.1044/nnsld11.4.5 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationTrack Citations ShareFacebookTwitterLinked In References Bose, A., Square, P. A., Schlosser, R., & van Lieshout, P. (2001). Effects of PROMPT Therapy on speech motor function in a person with aphasia and apraxia of speech. Aphasiology, 15, 767–785. Google Scholar Chumpelik, D. A. (1984). The PROMPT system of therapy. Seminars in Speech and Language, 5, 139–156. Google Scholar Freed, D. B., Marshall, R. C., & Frazier, K. E. (1997). Long term effectiveness of PROMPT treatment in a severely apractic-aphasic speaker. Aphasiology, 11, 365–372. Google Scholar Hayden, D., & Square, P. A. (1994). Motor speech treatment hierarchy: A systems approach. Clinics in Communication Disorders, 4, 162–174. Google Scholar Hayden, D. (1999). PROMPT manual level 1 and 2. Santa Fe, NM: PROMPT Institute. Google Scholar McNeil, M. R., Doyle, P. J., & Wambaugh, J. L. (2000). Apraxia of speech: A treatable disorder of motor planning and programming. In S. E.Nadeau, L. J.Gonzalez Rothi, & B.Crosson (Eds.), Aphasia and language: Theory to practice (pp. 221–266). New York: Guilford Press. Google Scholar Sparks, R., & Deck, J. (1986). Melodic intonation therapy. In R.Chapey (Ed), Language intervention strategies in adult aphasia (pp. 320–332). Baltimore, MD: Williams & Wilkins. Google Scholar Square, P. A., Chumpelik, D., & Adams, S. (1985). Efficacy of the PROMPT system of therapy for the treatment of acquired apraxia of speech. In R.Brookshire (Ed.), Clinical aphasiology (Vol. 15, pp. 319–320). Minneapolis, MN: BRK. Google Scholar Square, P. A., Chumpelik, D., Morningstar, D., & Adams, S. (1986). Efficacy of the PROMPT system of therapy for the treatment of acquired apraxia of speech: a follow up investigation. In R.Brookshire (Ed.). Clinical aphasiology (Vol. 16, pp. 221–226). Minneapolis, MN: BRK. Google Scholar Square, P. A., Martin, R. E., & Bose, A. (2001). The nature and treatment of neuromotor speech disorders in aphasia. In R.Chapey (Ed), Language intervention strategies in aphasia and related neurogenic communication disorders (pp. 847–884). Baltimore, MD: Lippincott, Williams & Wilkins. Google Scholar Square, P. A., Roy, E. R., & Martin, R. E. (1997). Apraxia of speech: another form of praxis disruption. In L. J. G.Rothi & K. M.Heilman (Eds.), Apraxia: The neuropsychology of action (pp. 173–206). Erlbaum, UK: Psychology Press Google Scholar Square-Storer, P. A., & Hayden, D. (1989). PROMPT treatment. In P. A.Square-Storer (Ed.), Acquired apraxia of speech in aphasic adults (pp. 190–219). UK: Lawrence Erlbaum. Google Scholar Yorkston, K., & Beukelman, D. (1981). Assessment of intelligibility of dys-arthric speech. Tigard, Oregon: C.C. Publications. Google Scholar Additional Resources FiguresReferencesRelatedDetails Volume 11Issue 4December 2001Pages: 5-8 Get Permissions Add to your Mendeley library History Published in issue: Dec 1, 2001 Metrics Downloaded 311 times Topicsasha-sigsasha-topicsasha-article-typesCopyright & Permissions© 2001 American Speech-Language-Hearing AssociationLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".