An accelerator-based neutron microbeam system for studies of radiation effects
Bibliographic record
Abstract
A novel neutron microbeam is being developed at the Radiological Research Accelerator Facility (RARAF) of Columbia University. The RARAF microbeam facility has been used for studies of radiation bystander effects in mammalian cells for many years. Now a prototype neutron microbeam is being developed that can be used for bystander effect studies. The neutron microbeam design here is based on the existing charged particle microbeam technology at the RARAF. The principle of the neutron microbeam is to use the proton beam with a micrometre-sized diameter impinging on a very thin lithium fluoride target system. From the kinematics of the ⁷Li(p,n)⁷Be reaction near the threshold of 1.881 MeV, the neutron beam is confined within a narrow, forward solid angle. Calculations show that the neutron spot using a target with a 17-µm thick gold backing foil will be <20 µm in diameter for cells attached to a 3.8-µm thick propylene-bottomed cell dish in contact with the target backing. The neutron flux will roughly be 2000 per second based on the current beam setup at the RARAF singleton accelerator. The dose rate will be about 200 mGy min⁻¹. The principle of this neutron microbeam system has been preliminarily tested at the RARAF using a collimated proton beam. The imaging of the neutron beam was performed using novel fluorescent nuclear track detector technology based on Mg-doped luminescent aluminum oxide single crystals and confocal laser scanning fluorescent microscopy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".