Research on Children With Cerebral Palsy in Low- and Middle-Income Countries
Bibliographic record
Abstract
The purpose of this special communication is to present ideas and thoughts from a symposium at the 75th Annual Meeting of the American Academy for Cerebral Palsy and Developmental Medicine. These included perspectives and lessons from 3 previously published review studies regarding cerebral palsy (CP) research in Brazil, India, and African countries, which explored the literature through the lens of the World Health Organization's International Classification of Functioning, Disability and Health (ICF) framework. Using this common lens, first we present the main findings of each of these articles, as well as the similarities and differences in CP research across these low- and middle-income countries (LMICs). Second, considering current evidence, lessons from other LMICs and based on our experiences, we raise recommendations of critical areas to be addressed such as ICF framework implementation and best evidence practice on CP, focusing on prevention, early diagnosis, and intervention (see Supplemental Digital Abstract, available at: http://links.lww.com/PPT/A413 ).
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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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".