Notice bibliographique
Résumé
Dr. John Prescott says that in his new role as chair of the Ontario Veterinary College's (OVC's) Department of Pathobiology, he plans to approach the job's challenges as he would a research problem in his bacteriology laboratory. “It's about logic and applied problem- solving,” he says. “First, you have to define the problem, (and determine) what options there are for investigation, then do the study and analyze the results. The biggest difference, the joker in the pack, which makes it so interesting, is that we're dealing with people, and the issues are also multiple and more complex.” Prescott began a 5-year term as chair of Pathobiology in September. Prescott joined the OVC in 1976 as a faculty member on contract in diagnostic bacteriology. He says that one of his goals in his new role is to continue to build the department's strength as a major centre for research and training in pathobiology by helping researchers acquire top-notch laboratory facilities and encouraging highly qualified students, especially veterinarians, to return for graduate study. “The field is changing because of the stunning new technologies,” he says. “I see our niche particularly in graduate-level training. We need to get highly- competent and well-trained people into the system within the different areas encompassed by this broad and diverse department.” The department already has 55 graduate students, and Prescott says it is bursting at the seams. “Funding to encourage graduate student enrolment by veterinarians is a challenge at the department, college, university, and the national level, as the next decade will bring more students in search of higher education, while many faculty members will be retiring.” He is enthusiastic about a recent announcement that the OVC has been approved as a training center for board certification by the American College of Laboratory Animal Medicine — the only certified training centre outside the United States. “This is a critical area that we have to develop nationally,” he says. “The chair's job is to help and encourage these types of initiatives to move forward.” As a personal interest, Prescott also sees opportunities for the department to play a larger role in investigating issues related to destruction of ecosystems, wildlife, and the environment. “I see this as a huge issue facing society,” he says. “We need to look at societal and global issues.” The department currently undertakes work in this area through associations with the Canadian Cooperative Wildlife Health Centre. Prescott will also be busy helping the department to plan for a new pathobiology building on Gordon Street, while continuing to meet other research and teaching commitments. Although his research and teaching responsibilities may be more limited during his 5-year term as chair, Prescott hopes to continue to teach bacteriology to DVM students and to conduct research in bacterial diseases in animals, including Rhodococcus equi pneumonia. (by Karen Gallant, Communications Officer, Ontario Veterinary College, University of Guelph)
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 | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,002 |
| Communication savante | 0,007 | 0,003 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,236 | 0,066 |
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 ».