SUDBIOTECH: A Training Initiative in Plant Biotechnology Dedicated to Scientific Communities in Developing and Emerging Countries
Notice bibliographique
Résumé
The SudBiotech project is targeting PhD and Masters Programmes in Universities and Excellence Research Centres located in developing countries. It proposes an integrative and multidisciplinary approach under the form of a one-week discovery and training itinerary. SudBiotech is aimed at addressing various different fields of Plant Biotechnology, under the specific socioeconomic context of scientific communities from these countries. Our main goal is to train students, research staff, deciders, professionals and journalists to the basic knowledge underlying applications of plant biotechnologies, in order to both update the amount of knowledge which is requested at Master’s level and to acquire a solid body of information which is indispensable for any decision making, in a field of research which is often the target of political, social and media-related pressure. The team of Professors involved in the project shares a strong experience in teaching and training in overseas French Speaking Universities (AUPELF-UREF projects in Marocco, Tunisia, Togo, Côte d’Ivoire, TEMPUS Programme in Lebanon, AUF-Actions de Recherche en Réseau in Benin). The team is composed of senior scientists acting in various complementary fields, namely: Biochemistry/Physiology (A. Nato), Plant Breeding/Molecular Biology (Y. Henry), Tropical Agriculture/Epigenetics (A. Rival). Thanks to these complementarities, SudBiotech is able to propose a training itinerary which is diversified and integrated, covering areas from the plant cell and its original potentialities to the most recent industrial applications of plant biotechnologies (GMOs), their public acceptance in developing and emerging nations and their applicability to tropical plant commodities. The training offer is amplified and enriched through the active role of local research and training staff, who are encouraged to actively participate in the SudBiotech project under various forms including lectures, field visits, practical sessions, etc. SudBiotech relies on original research results, which support and illustrate the various different basic notions evoked during lectures. The case of the bio-production of high added value pharmaceutical products by genetically engineered cells or plants under confined condition is a good example of this integration. Our priority is to establish a long-term, continuous system for training and capacity building, based on appropriate tools for scientific communities in developing and emerging countries: training of PhD students, job opportunities in their native country/region, overseas training, access to scientific information and literature and access to funders and international networks. It is important to note that any training material which is produced under the framework of SudBiotech is graciously given without any Intellectual Property Rights to partner institutions, in order to constitute a local basis for training in Plant Biotechnologies in beneficiary countries.
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 | 0,005 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,035 | 0,008 |
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 ».