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Record W1979594704 · doi:10.1002/mrm.21140

Thomas Raidy, Ph.D.

2006· article· en· W1979594704 on OpenAlexaboutno aff
Christopher H. Sotak, Susan J. Kohler

Bibliographic record

VenueMagnetic Resonance in Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsFood and drug administrationLibrary scienceManagementMedicineChemistryComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0960.075

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.314
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2006
Admission routes1
Has abstractyes

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