Postinjection attenuation correction using singles transmission on a positron tomograph without interplane septa
Bibliographic record
Abstract
Singles transmission is ideally suited for attenuation correction on PET scanners without interplane septa, producing low dead time and no randoms. However, sinogram windowing can not be used in singles mode to reject scatter or the emission background activity which is present after isotope injection. The authors propose that a simple subtraction of the singles emission background from the singles transmission scan will produce an accurate attenuation correction. The emission background is measured by performing an additional singles mode scan, but without actually exposing the /sup 137/Cs point source. Phantom studies with uniform cylinders show that the measured attenuation coefficients are restored to the true values after the emission background is subtracted. The effect on noise equivalent count rate is analogous to randoms subtraction because the singles emission background is relatively uniform throughout the field of view. The time required to perform a postinjection transmission scan is increased over a preinjection scan because the singles emission background must be measured separately.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".