Horizons in nuclear medicine and molecular imaging: highlights of the Third Gulf Nuclear Medicine Conference.
Bibliographic record
Abstract
The Third Gulf Nuclear Medicine Conference took place in the state of Kuwait at Salwa Al Sabah hall, Safir marina hotel in Salmiya. The event extended from March 29th to April 1st 2009. The assembly was a great chance for all nuclear medicine, i.e. physicians, technologists and researchers in the field to meet and exchange experience and knowledge. The number of participators registered for this conference was beyond expectations; total registrants of 611 attended the event and actively end it. The conference was attended by international, regional and local participants. There were 23 speakers, including 13 invited guest speakers who came from USA, Canada, Europe and the Gulf region. In addition to the lectures and oral presentations, there were 30 poster presentations. The latest updates in the field together with most recent findings in the participants' own research were presented. The lectures and posters covered different basic and clinical categories of nuclear medicine. This article summarizes the highlights of the major topics discussed with some recommendations when applicable. Proceedings of the conference can be found in the World Journal of Nuclear Medicine of April, 2009.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".