Bibliographic record
Abstract
All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Can adian Medical Association. 1676 CMAJ, October 4, 2011, 183(14) © 2011 Canadian Medical Association or its licensors Irecall precisely two lectures on nutri-tion in medical school. True, weheard physiology lectures on short-chain fatty acids, and our biochemistry professors encouraged us to remember the structures of the amino acids, but just how these things related to what a person should eat remained largely indecipher-able. One was left with the impression nutrition didn’t matter all that much. Or if it did, it was common sense stuff we knew already: Eat your vegetables; lay off the red meat, fat and salt. It seems my medical education was not unusual. As early as 1966, Robert Shank complained in the pages of the American Journal of Public Health1 that “there is inadequate recognition, support, and attention given ” to nutrition in med-ical schools. Fast-forward nearly 50 years, and it seems little has been done to fill the hole. A recent survey of Canadian medical students2 revealed that, while they felt comfortable advising patients about basic nutrition and disease preven-tion, they were uncomfortable discussing the role of nutrition in disease treatment and with finding credible sources of nutrition information. Nearly 90 per cent felt they needed more nutrition education during medical school. So why has noth-ing changed?
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".