Notice bibliographique
Résumé
It is with great sorrow that we note the recent untimely death of Tom Raidy, a long-time friend and significant contributor to our field. Tom received his Ph.D. in Chemistry from the University of Waterloo in Canada. Tom served as an Assistant Professor of Chemistry at the University of South Carolina at Aiken as well as a Research Assistant Professor of Chemistry at the University of South Carolina at Columbia, working with Paul Ellis. In the mid-1980s, Tom joined the engineering staff at what was then GE NMR Instruments, in Fremont, CA. Although Tom always considered himself a “theoretician,” he developed exceptional expertise in both the software and hardware aspects of MR engineering. For example, Tom was one of the key figures on the engineering team that developed the second-generation of GE's animal-imaging MR instrument; the Omega. Thomas Raidy, Ph.D. In the late 1980s, Tom joined the GE Medical Systems group in Waukesha, WI, where he subsequently became the engineering manager for the Signa Spectroscopy product. Tom had a seminal role in the development of GE's automated proton spectroscopy package, which was first described in Magnetic Resonance in Medicine 1994;31:365–373. The PROBE (proton brain exam) spectroscopy option was the first truly push-button clinical MRS exam, providing information about localized brain chemistry in less than 10 min. PROBE was granted U.S. Food and Drug Administration (FDA) marketing clearance in June of 1995 and was approved as a reimbursable procedure the following year. Again, Tom was one of the major driving forces in these efforts. For many years following its introduction, PROBE was the only clinical spectroscopy option of its kind and remains one of the leading products in the industry. PROBE has been installed on hundreds of 1.5-T and 3-T MR systems around the world and played an essential role in establishing proton MRS as an important adjunct to a clinical MR exam. After a successful industrial career at GE, Tom had recently returned to academics. Tom held the position of Clinical Associate Professor in the Department of Radiation Oncology at the Duke University School of Medicine. Tom played a critical role in a variety of clinical research projects in the department and his invaluable MR expertise will surely be missed. Following his move to Duke, Tom also served as an expert reviewer for Magnetic Resonance in Medicine. For those of us that knew or interacted with Tom, he was a man of exemplary integrity and generosity. Both clinical MR users and his academic colleagues will remember Tom as a consummate professional, whose selfless dedication was unrivaled by many in the field. Tom was also a devoted family man and is survived by his wonderful wife, Laurel, and their three adult children Tom, Vanessa, and Aidan. Our condolences go out to them for their loss. As many of his colleagues have noted, Tom was “one of the good guys”—we could not agree more. Our field has suffered a great loss in Tom's passing; however, his example will hopefully carry on through those of us who knew him as a colleague and a friend.
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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,096 | 0,075 |
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 ».