<i>Nutrition Services in</i>Canadian Neonatal Follow-up Programs
Bibliographic record
Abstract
The benefits of nutrition assessment and support of the high-risk infant are well established. The premature infant remains vulnerable for poor growth and developmental disabilities, thus requiring consistent monitoring, intervention, and follow-up care. The purpose of this study was to determine the registered dietitian's role in neonatal/perinatal follow-up programs. A survey was sent to the 26 follow-up programs in Canada. The questionnaire response rate was 81%. Registered dietitians were involved in 67% of these programs. Of these dietitians, 43% were assigned to neonatal/perinatal follow-up programs while 57% were involved only by consult. The average time that assigned registered dietitians devoted to programs was 0.35 full-time equivalents. Over 80% of the dietitians did ongoing development, evaluation, and modification of nutrition care plans; 71% screened new patients for nutritional risk, and 100% instructed patient families and developed teaching materials. The study findings will assist program planners who wish to establish a dietitian position in a neonatal/ perinatal follow-up program. For registered dietitians already working in such programs, the results may provide some guidance on role definition and expansion.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".