Notice bibliographique
Résumé
Dr. Keith Prasse is a very distinguished leader in veterinary education. He started his career achieving his BS and DVM degrees from Iowa State University (ISU). He returned to ISU after a brief period in private practice in Illinois. His well-recognized career in veterinary pathology began with his MS and PhD degrees, followed by a five-year period of teaching at ISU. Dr. Prasse joined the faculty of the University of Georgia in 1972, and thus began a long-term partnership with Dr. Bob Duncan that is arguably the foundation of veterinary clinical pathology. The textbook they authored, Veterinary Laboratory Medicine: Clinical Pathology, or "Duncan and Prasse" as it is known, remains the standard today, with later participation from Dr. Ed Mahaffey and most recently Dr. Ken Latimer. Dr. Prasse has mentored numerous graduate students and received many awards over his 23-year career in teaching, including the Norden Distinguished Teaching award twice, once at ISU and once at Georgia. His leadership as President of the American College of Veterinary Pathologists was greatly acknowledged and appreciated. Dr. Prasse's administrative service at the University of Georgia spanned 14 years, first as Associate Dean for Public Service and Outreach and later as Dean for eight years, during which time he served as President of the Association of American Veterinary Medical Colleges (AAVMC). The growth of the College of Veterinary Medicine under Dean Prasse's visionary leadership was extraordinary. He led through difficult economic and political times, yet the college and its community continued to prosper. His legacy at the University of Georgia is indelible and perpetual. His outstanding leadership of the college was recognized by the Georgia Veterinary Medical Association in 2004, when he was given the Georgia Veterinarian of the Year award. Since his retirement from Georgia, Dr. Prasse has contributed greatly to the profession and to the AAVMC by leading the Foresight project. Dr. Prasse honored those attending the 2009 AAVMC Symposium by giving the Recognition Lecture. As always, his address was inspirational, and the substance of it is included here. -Sheila W. Allen, Dean, University of Georgia College of Veterinary Medicine.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 tête enseignante, 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 ».