Effect of an aerosol deposition pattern in the lung on the counting efficiency of a large area germanium detector array
Bibliographic record
Abstract
The Human Monitoring Laboratory has extended the use of sliced lungs containing planar sources to simulate heterogeneous radionuclide deposition patterns. This work examined two deposition patterns and their effect on the counting efficiency of low-energy photons. The results have shown that heterogenous distributions can be difficult to detect in some cases and can still lead to large uncertainties (up to a factor of 2.5) in the activity estimate, especially at low photon energies. At higher energies ( approximately 60 keV), the effect of the heterogeneous distribution is greatly reduced and errors in the activity estimate reduced to approximately 25%. The presence of a heterogenous distribution can be detected by comparing the ratio of the individual detector counts with the expected values obtained from measuring multiple lungs sets that contained a homogeneous distribution. The distributions tested in this paper were detectable (at 2sigma) as heterogeneous by two of the four detectors in the counting array.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".