Identification of oxygen-19 during<i>in vivo</i>neutron activation analysis of water phantoms
Bibliographic record
Abstract
Hand bone equivalent phantoms (250 ml) carrying selenium in various amounts were irradiated and counted for in vivo neutron activation analysis (IVNAA) by employing a 4π NaI(TI) based detection system. During the analysis of counting data, a feature at a higher energy than the gamma ray peak from (77m)Se (0.162 MeV) was observed at 0.197 MeV. Further investigations were made by preparing water phantoms containing only de-ionized water in 250 ml and 1034 ml quantities. Neutrons were produced by the (7)Li(p,n)(7)Be reaction using the high beam current Tandetron accelerator. Phantoms were irradiated at a fixed proton energy of 2.3 MeV and proton currents of 400 μA and 550 μA for 30 s and 22 s respectively. The counting data saved using the 4π NaI(TI) detection system for 10 s intervals in anticoincidence, coincidence and singles modes of detection were analyzed. Areas under gamma peaks at energies 0.197 MeV and 1.357 MeV were computed and half-lives from the number of counts for the two peaks were established. It was concluded that during neutron activation of water phantoms, oxygen-18 is activated, producing short-lived radioactive 19O having T(1/2) = 26.9 s. Induced activity from 19O may contribute spectral interference in the gamma ray spectrum. This effect may need to be taken into account by researchers while carrying out IVNAA of biological subjects.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".