The Thailand Declaration of the International College of Nutrition; Can Functional Foods and Functional Crops Decrease the Risk of Chronic Diseases and Provide Wellness?
Bibliographic record
Abstract
There is evidence that optimal nutrition is fundamental to human health and in the prevention of non-communicable diseases (NCDs) later in adult life. The identification, production and consumption of functional foods worldwide can increase health benefits for all who can access and afford such foods subject to advice from nutritionists. Recent meetings organized by the health agencies, give a crucial opportunity to make nutrition, a central part of the post-2015 sustainable human and agricultural development agenda. The aim of discussions in these meetings was to provide functional crops and foods to achieve optimal health by prevention of NCDs. It is possible that these efforts might ensure that the goals and targets set in the agenda are adequate to address the many challenges of global undernutrition as well as obesity which are major risk factors of NCDs. In many developing and middle income countries, food security provided by the governments, in one sense understandably, gave least consideration to functional foods supply and the prevention of obesity and metabolic syndrome, resulting in to emergence of NCDs. The Thailand Declaration reiterates that commitments to eradicate hunger and undernutrition as well as over-nutrition, and to increase investments in effective interventions; designers foods and designers crops. However, in planning coherent policies, our past experience on rapidly absorbed, energy-rich processed foods should be taken in to account while developing sustainable food systems. The food industry should be educated to exploit the expertise of food scientists and health professionals in designing functional foods taking cognizance of manufacturing and processing. Similarly, agriculture scientists may be actively involved in educating farmers so as to grow cash crops providing functional foods. The aim should be to achieve an increase in the availability of functional foods to an extent, or by a policy, by which such foods are available to poors, at affordable cost to prevent hunger and undernutrition and related diseases as well as NCDs. In addition our efforts might help in developing an international consensus on how to approach the development of new designer foods by farmers and food industry to produce low glycemic index foods. Such efforts may establish an international framework for the prevention of NCDs, so that human susceptibility to these diseases is substantially diminished.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.013 | 0.008 |
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".