Nutrition and Brain Function: A Multidisciplinary Virtual Symposium
Bibliographic record
Abstract
A few months ago, the Brazilian Society for Neuroscience and Behavior (SBNeC) promoted a "virtual symposium" (by Internet, under the coordination of R.C.A. Guedes) on "Nutrition and Brain Function". The discussions generated during that symposium originated the present text, which analyzes current topics on the theme, based on the multidisciplinary experience of the authors. The way the brain could be non-homogeneously affected by nutritional alterations, as well as questions like early malnutrition and the development of late obesity and hormone abnormalities were discussed. Also, topics like the role of essential fatty acids (EFAs) on brain development, increased seizure susceptibility and changes in different neurotransmitters and in cognitive performance in malnourished animals, as well as differences between overall changes in nutrient intake and excess or deficiency of specific nutrients (e.g. iodine deficiency) were analyzed. It was pointed out that different types of neurons, possibly in distinct brain structures, might be differently affected by nutritional manipulation, including not only lack-but also excess of nutrient intake. Such differences could help in explaining discrepancies between data on humans and in animals and so, could aid in determining the basic mechanisms underlying lesions or changes in brain function and behavior.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".