Measurement of $$\alpha $$-particle quenching in LAB based scintillator in independent small-scale experiments
Bibliographic record
Abstract
The $$\alpha $$ -particle light response of liquid scintillators based on linear alkylbenzene (LAB) has been measured with three different experimental approaches. In the first approach, $$\alpha $$ -particles were produced in the scintillator via $$^{12}$$ C(n, $$\alpha $$ ) $$^9$$ Be reactions. In the second approach, the scintillator was loaded with 2 % of $$^{\mathrm {nat}}$$ Sm providing an $$\alpha $$ -emitter, $$^{147}$$ Sm, as an internal source. In the third approach, a scintillator flask was deployed into the water-filled SNO+ detector and the radioactive contaminants $$^{222}$$ Rn, $$^{218}$$ Po and $$^{214}$$ Po provided the $$\alpha $$ -particle signal. The behavior of the observed $$\alpha $$ -particle light outputs are in agreement with each case successfully described by Birks’ law. The resulting Birks parameter kB ranges from $$(0.0066\pm 0.0016)$$ to $$(0.0076\pm 0.0003)$$ cm/MeV. In the first approach, the $$\alpha $$ -particle light response was measured simultaneously with the light response of recoil protons produced via neutron–proton elastic scattering. This enabled a first time a direct comparison of kB describing the proton and the $$\alpha $$ -particle response of LAB based scintillator. The observed kB values describing the two light response functions deviate by more than $$5\sigma $$ . The presented results are valuable for all current and future detectors, using LAB based scintillator as target, since they depend on an accurate knowledge of the scintillator response to different particles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".