Estimating a risk exposure on biogenic amines trough surveys on the population and contents in foods and beverages
Notice bibliographique
Résumé
As part of its mission, ISEKI-Food Association establishes and maintains a network among universities, research institutions, and companies in the food chain in addition to working to ensure that food studies are of high quality.However, we must also begin planning how to gear science, education, and the food industry to meet the needs of future generations as well as how to contribute to the sustainability of our planet by these food actors.In light of this, the 7 th International ISEKI-Food Conference, which had as main theme "NEXT-GENERATION OF FOOD RESEARCH, EDUCATION AND INDUSTRY", focused on future challenges in education on food science and technology, in research activities related to processing, quality and safety, packaging of foods and in societal engagements in the field divided in three main sections: EDUCATION: CHALLENGES OF EDUCATION IN A CHANGING WORLD; RESEARCH: NEXT GENERATION OF FOODS; and SOCIETY ENGAGEMENT: SOCIETY AND FOOD INDUSTRY.The conference was dedicated to all food actors, creating bridges among them.The delegates had the opportunity to exchange new ideas and experiences face to face, to establish business or research relations, and find global partners for future collaborations.We were privileged to host the following keynote speakers: HUGO DE VRIES from INRAE, France, talked about "FOODPathS towards sustainable outcomes"; JESPER TÆKKE from Aarhus University, Denmark whose talk was about "Digitalization of education -the theory of the three waves"; LAURENT GUILLIER from ANSES, France informed us on "Challenges and perspectives in food safety"; GILLES TRYSTRAM from AgroParisTech, France, presented "Some research questions in food and biotechnological process engineering"; HORST-CHRISTIAN LANGOWSKI from Fraunhofer Institute, Germany, talked about "Circular Economy for Plastic Food Packaging -Options and Challenges"; CATHERINE BAYARD from Givaudan Naturals, France, questioned us "Are you ready for the future of dairy alternatives?";MAURO SERAFINI from Teramo University, Italy, spoke about "Functional food and health: essentiality of human evidence"; STELLA CHILD from GFI Europe, Belgium informed us on "The 3 pillars of future protein production: Plant-based, cultivated, and fermentation-made meat, eggs and dairy" and FERRUH ERDOGDU from Ankara University, Türkiye presented the "Future of Food Engineering in the Digitalization Era -Preparing for Industry X.0".There were 244 abstracts submitted and accepted!Among them, 80 were selected to be oral presentations and all the others poster presentations.The abstracts of the keynote speakers together with the abstracts of the oral and poster presentations can be found in this Book of Abstracts.The authors of the best oral and poster presentations have the possibility to publish their works in the Food and Bioproducts Processing Journal, in the International Journal of Food Studies, and in a book published by Springer entitled NEXT-GENERATION OF FOOD RESEARCH, EDUCATION AND INDUSTRY.We would like to express our sincere appreciation to all participants, speakers, and contributors for their valuable inputs to the success of the 7 th International ISEKI-Food Conference.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».