Notice bibliographique
Résumé
A s an innovative researcher, dedicated teacher, astute clinician, and capable leader, J. Gregory Fitz, "Greg" (Fig. 1), has made significant contributions to the science and practice of hepatology and now continues to advance the mission of the AASLD as president of the organization.Greg was born in Lakeland, Florida, although shortly after his birth the family moved to Hickory, North Carolina.Greg's father was a cardiologist, the first in Hickory, and a prominent member of the community who soon became a member of the North Carolina Medical Board.Hickory is a small town located near the mountains of western North Carolina.Known for its handmade furniture and textile industry, its proximity to the Appalachian Mountains provides a myriad of outdoor opportunities; growing up in this beautiful area of the country, it is easy to understand Greg's lifelong passion for the outdoors.Shortly after arriving in Hickory, Greg was enrolled in the local kindergarten where he met his wife-to-be, Linda.In fact, he and Linda would go on to attend elementary school, high school, and even college together.Linda states that, as a child, "Greg was involved in everything"; an active member of the student body, president of the student council, wrestler, and high school football player.After high school he and Linda attended the University of North Carolina at Chapel Hill (UNC) where Greg majored in Chemistry and Linda in Special Education.Greg graduated from UNC summa cum laude as a Morehead scholar and, as a crowning achievement to his early successes, he and Linda were married.Greg's father was a significant influence in his decision to become a physician, as well as his decision to attend Duke University for medical school.The Fitz's had a strong history at Duke University, his father was also a Duke graduate and his mother previously worked for Dr. Eugene Stead, the Chair of Internal Medicine and a renowned medical educator, researcher, and founder of the Physician Assistant profession.Greg did not follow in his father's footsteps to become a cardiologist, however.In fact, Greg's early interest during medical school was in neurology and he worked in the laboratory of Dr. McNamara, performing research in experimental models of epilepsy.The young, aspiring researcher received the "Best Research Award" from the Epilepsy Foundation of America for this work.While it did not inspire a career as a neuroscientist, it nonetheless formed the foundation for his lifelong interest in ion channels and electrophysiology-the focus of his research activities for years to come.Greg graduated from Duke medical school AOA (Alpha Omega Alpha), gave the class graduation speech, promptly moved with Linda and their new daughter, Rebecca, from the east coast to the west coast, and entered the Internal Medicine residency program at the University of California at San Francisco (UCSF).Greg recalls that UCSF was an excellent training venue where residents worked independently and were given significant leadership opportunities early in their careers.Greg successfully completed his residency in Internal Medicine, spent a year as Chief Resident, and then became the Assistant Chief of Medicine.He was recognized at this early stage in his Fig. 1.
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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,062 | 0,021 |
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 ».