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Record W4383868491 · doi:10.1002/mp.15993

Past AAPM President: 2002

2023· editorial· en· W4383868491 on OpenAlexaboutno aff
Robert G. Gould

Bibliographic record

VenueMedical Physics · 2023
Typeeditorial
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsnot available
FundersUniversity of California, San FranciscoHarvard UniversityRadiological Society of North America
KeywordsMedical physicistNuclear medicineMedicineMedical physicsLibrary scienceComputer science

Abstract

fetched live from OpenAlex

I am Robert Gould and a professor emeritus in the Department of Radiology & Biomedical Imaging, University of California San Francisco (UCSF). My duties at UCSF included clinical activities and academic research and I had significant responsibilities for implementing the Department's PACS infrastructure. I joined the AAPM in 1972 as a graduate student at the University of Pennsylvania in a medical physics program directed by Dr. John Hale, the third president of the AAPM. In 1974, I moved to a medical physics program at Harvard University directed by Dr. Bengt Bjarngard, the 20th president of the AAPM. My thesis advisor at Harvard was Dr. Edward Webster, the fifth president of the AAPM. My first major position within the AAPM was that of Scientific Program Director for the 1986 annu meeting held in Lexington, KY. I remained active on the Program Committee, chairing it from 1993 to 1998 and was the AAPM Scientific Program director on the Radiological Society of North America Program Committee from 1994 to 1998. I became president of the AAPM in 2002 with the Society approaching a membership count of 5000 and an annual budget of approximately 5 million, reflecting a robust and growing society. It was the year in which an alignment was agreed to between the AAPM and ACMP on examining boards. A concern, which extended over a number of years, was that while the Annual Meeting was growing, the participation of diagnostic imaging physics was declining reflected in the number of proffered diagnostic abstracts decreasing by about 50% over the previous 5 years. In a multi-year effort to strengthen the participation of diagnostic medical physicists at the Annual Meeting, and to better coordinate between scientific, educational, technical, and social components of the meeting, the Meeting Coordination Committee was formed in 2001, with 2002 as the first Annual Meeting under its guidance. Another challenge was that Sol Trofi, Jr., the Executive Director of the AAPM starting in 1994 and under whose guidance the AAPM prospered, announced his retirement at the end of 2003 but presented a transition plan where Angela Keyser, his Deputy Executive Director, would take his position. The Board approved this promotion and Angela has proved to be a superb choice. The 2002 Annual Meeting was held in Montreal, Canada as a joint meeting with the Canadian Organization of Medical Physics and, certainly in part due to the Canadian participation, had a record number of scientific abstract submissions (750) and an increased percentage of diagnostic abstracts. The Presidential Symposium was titled “Perspectives on Radiation Exposure” and speakers included John Cameron and Bernard Cohen. The Local Arrangement Committee was headed by Ervin Podgorsak, the 2007 Coolidge Award winner, and included a concert in the Notre Dame Basilica and a memorable dinner and entertainment with acrobatics and a Celine Dion impersonator. I am privileged to have been a president of the AAPM and feel the Society benefits its members scientifically and professionally and personally. Contacts I made through participation in AAPM Committees and as President helped in my academic advancement, in my understanding of professional challenges faced by basic scientists in an MD environment, and created lasting friends.

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)0.003
metaresearch head score (Gemma)0.009
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: Editorial · Consensus signal: none
Teacher disagreement score0.345
Threshold uncertainty score0.934

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0130.004
Open science0.0020.002
Research integrity0.0110.007
Insufficient payload (model declined to judge)0.3450.444

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 head0.013
GPT teacher head0.301
Teacher spread0.288 · 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
GenreEditorial

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

Citations0
Published2023
Admission routes1
Has abstractyes

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