2015 Section on Pediatrics Knowledge Translation Lecture
Bibliographic record
Abstract
In Brief Key Points: Until recently, the incidence and effect of vestibular system impairments in children has been grossly underidentified and thus not addressed. Because of incidence reports (approximately 10% of the US population younger than 21 years) and evidence of the efficacy of evaluation methods and interventions, researchers and clinicians are focusing on development of optimal interventions to enhance function, thus minimizing the negative effect of vestibular hypofunction on reading, motor development, and postural control. However, research progress has been slow. How can clinicians and researchers collaborate so that (1) vestibular deficits and related impairments can be identified in children, and (2) optimal interventions can be identified and implemented so that children with peripheral and/or central vestibular dysfunction can benefit? Summary: Our participation in knowledge translation is presented, to include discussion of possible barriers, challenges, and opportunities for facilitating collaboration and joint efforts of clinical and research practice. The authors illustrate how clinicians and researchers can collaborate to identify vestibular deficits and related impairments and optimal interventions so that children with peripheral and/or central vestibular dysfunction can benefit.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".