Novel application of the 8 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si44.svg" display="inline" id="d1e649"> <mml:mi>π</mml:mi> </mml:math> gamma-ray spectrometer for 3 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si24.svg" display="inline" id="d1e654"> <mml:mi>γ</mml:mi> </mml:math> positron emission tomography
Bibliographic record
Abstract
In tissue, approximately 0.5% of positron annihilations emit three γ rays instead of the usual two. Although these events are not currently used for imaging in Positron Emission Tomography (PET) scans, they can provide valuable diagnostic information on tissue properties such as porosity and hypoxia. The present work demonstrates an approach for imaging 3 γ positron annihilations from β + decays of 18 F. The isotope is produced through a novel method of neutron activation of a polytetrafluoroethylene (Teflon) disk. Measurements were performed using the 8 π gamma-ray spectrometer, a highly efficient and selective ball array of 72 Bismuth Germanium Oxide (BGO) detectors arranged in an icosahedron geometry with ∼ 95% solid-angle coverage. Coupled with a digital data acquisition system, the 8 π spectrometer provides waveform digitization and online multiplicity filtering capabilities, enabling efficient and selective measurement of rare 3 γ positron annihilations. An energy-based reconstruction method was applied to produce three-dimensional 3 γ PET images with a FWHM point spread of 4.0 cm at the center of the array.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".