Nutritional Status at Diagnosis in Children With Cancer. 2.
Bibliographic record
Abstract
Assessment of nutritional status in children with cancer is important but measures based on weight can be problematic at diagnosis, especially in those with advanced disease. Likewise, dual energy x-ray absorptiometry may be confounded by other radiological procedures and is not commonly available in low-income countries where most children with cancer live. Arm anthropometry is not subject to these constraints. In a study sample of 99 Canadian patients with cancer at diagnosis, mid-upper arm circumference correlated well with lean body mass as measured by dual energy x-ray absorptiometry but triceps skin fold thickness was a poor predictor of fat mass. Arm anthropometry can be a useful tool for the measurement of nutritional status in children with cancer. However, further studies, particularly in low-income countries and in children with solid tumors at diagnosis, are required to determine the full extent of its utility.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 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".