Availability of Nutrition Screening Parameters: In New Brunswick Hospitals and Nursing Homes
Bibliographic record
Abstract
We explored the availability of parameters for a nutrition screening system among elderly people in New Brunswick (NB) health care facilities. Patients aged 65 or older were asked to participate in the study; each participant had been admitted to one of four hospitals or lived in one of six nursing homes. Availability of nutrition screening parameters (weight, height, weight change, serum albumin level, appetite, and food intake record) was assessed by auditing the participants' medical charts. When data were not available, the feasibility of obtaining them was determined. Additional data related to nutrition screening were also obtained. In total, 421 participants were recruited for the study: 140 (33.2%) who lived in nursing homes and 281 (66.8%) who were in hospitals. Parameters needed to conduct nutrition screening, such as weight upon admission, were available for 83.6% of participants; usual weight was available for 43.0%, height for 86.0%, and serum albumin level for 47.5%. Our findings show that basic parameters for nutrition screening are available, and that implementation of a nutrition screening system is feasible for patients in NB health care facilities.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".