Long-Term Neuromotor Speech Deficits in Survivors of Childhood Posterior Fossa Tumors: Effects of Tumor Type, Radiation, Age at Diagnosis, and Survival Years
Bibliographic record
Abstract
The cerebellum is important for the coordination of fluent speech. The authors studied how childhood cerebellar tumors affect long-term neuromotor speech outcomes, including the relation between outcome and tumor type, radiation, age at diagnosis, and survival years. Videotaped speech samples of child and adult long-term survivors of childhood cerebellar astrocytoma (nonradiated) and medulloblastoma (radiated) tumors and healthy controls were analyzed by 2 speech pathologists for ataxic dysarthria, dysfluency, and speech rate. Ataxia varied with tumor type/radiation. Medulloblastoma survivors had significantly more ataxic dysarthric features than either survivors of astrocytomas or controls, who did not differ from each other. Dysfluency varied with a history of a posterior fossa tumor. Medulloblastoma and astrocytoma survivors were each significantly more dysfluent than controls but did not differ from each other. Speech rate varied with age and tumor type. Adult controls were significantly faster than child controls, although adult tumor survivors were comparable to their child counterparts. Adult controls had significantly faster speech rates than adult survivors of medulloblastoma tumors. Ataxic dysarthric speech characteristics are more frequent in radiated survivors of medulloblastoma tumors than nonradiated survivors of astrocytoma tumors. Dysfluent and slow speech occur in cerebellar tumor survivors, regardless of tumor type and radiation history. Cerebellar tumors in childhood limit speech rate in adulthood.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".