A Comparison of Adolescents Consumption of Micro and Macro Nutrient Rich Foods
Bibliographic record
Abstract
The study involves a comparison of pupils’ consumption of macro and micro nutrient rich food as well as healthy and less healthy snacks after being exposed to a teaching model on balanced diet developed by the researcher which takes into cognisance pupils’ prior knowledge of healthy eating. Healthy snacks are snacks that are low in fat and sugar while less healthy snacks are snacks that are high in fat and sugar. The study was carried out in Britain, United Kingdom in summer term of 2007. Participants were year 7 pupils of Ceredigion Local Education Authority in rural Mid-Wales, they were requested to fill-in a Food Diary of food consumed at breakfast, lunch and dinner times including mid-morning and mid-afternoon snacks for five days (Thursday to Monday). This is to include both food consumed at home at weekend as well as school meals consumed at school during weekdays. There was evidence of increase of consumption of healthy snack as well as the consumption of macro nutrients (carbohydrate, fat and protein) and micro nutrients (vitamin, mineral and fibre); all six classes of food that makes up a balanced diet [1] after the intervention compared to before the intervention, although the rate of increase in the consumption of micro nutrient was not statistically significant compared to the increased in the consumption of macro nutrient. This study revealed that though the teaching model was able to alter eating behaviour in the desired direction of healthy eating which is the consumption of micro nutrient. More has to be done to encourage adolescents to consume more vitamin, mineral and fibre rich food items.
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 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 | 0.001 |
| 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) | 0.002 | 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".