Bibliographic record
Abstract
<p>This Issue of the Journal of Food Research, dedicated to the IX Italian Congress on Food Chemistry, ChimAlSi 2012 (Ischia, Napoli, Italy-June 3-7), collects selected manuscripts presented at the Congress, and proposes some aspects and an in depth look of many subjects related to food, that have been the focus of the ChimAlSi 2012. The Scientific Committee, formed by Proff. Ettore Novellino, Luca Rastrelli, Alberto Ritieni, and Antonello Santini, made this event unique as it has been enriched by the participation of more than 300 delegates, including many young researchers from different Countries. On behalf of the Scientific and Organizing Committes, I would like to take the chance to thank here all the speakers and the partecipants, that gave their valuable contribution to the brilliant success of this scientific event. The Congress represented a challenging chance for scientists, regulators, and industry representatives, to meet and share aspects of cutting edge knowledge in the field of Food Chemistry, new research lines, and potential development opportunities to provide the market with higher quality food and nutraceuticals. The IX Italian Congress of Food Chemistry included 12 plenary lectures, 66 lectures, and 290 poster presentations. Two Workshops focused on food contaminants and on the role of food in human health, completed the program of the activities, that covered a wide variety of food related topics ranging from food contaminants and food quality to new analytical approaches, nutritional and health aspects, food integrators, medical foods, nutraceuticals. The scientific contributions were divided in four homogeneous sessions dedicated to food safety, techniques of food analysis, bioactive compounds, and nutraceuticals. These last food-derived compounds, mostly of vegetal origin, are starting to be considered the challenge for the future in the field of Food Chemistry and Nutrition, as a valid low cost, environmental friendly sources alternative to drugs as active supplements for the prevention and to support the therapy in many different health conditions.</p>
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 | 0.005 | 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 | 0.001 |
| 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 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".