TO STUDY THE RELATIONSHIP BETWEEN JUNK FOOD ADVERTISEMRNT AND PURCHASING BEHAVIOUR OF TEENAGERS (HARYANA)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Junk refer to food that is high in calories but low in nutritional content and something that is appealing or enjoyable but of little or no value. Junk food easily available in market at different cost. Junk food is not good for health because it contains high amounts of fat or sugar. Various type of Junk food that available in restaurants like cold-drinks, chips, chocolates, and candy etc. The number of junk food restaurants and chain is increasing because people around the world like to eat junk food. USA, Canada, Britain, Australia, Japan, Sweden etc. are the countries with most junk food consumption around the world. Junk food is more popular because of experience of great taste, better shelf life and easy transportation. The junk food advertising is also play a great role in junk food’s popularity. But it should be avoided, because of lack of energy, high cholesterol and poor concentration. It causes a lot of harmful effect on the body like obesity, diabetes, heart disease and various types of skin cancers. Eliminating the temptation for junk food and developing the awareness for fitness can be helping in avoid the junk food from the healthy diet regimen.
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.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 it