Direct measurement of the bubble-nucleation energy threshold in a<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>CF</mml:mi><mml:mn>3</mml:mn></mml:msub><mml:mi mathvariant="normal">I</mml:mi></mml:math>bubble chamber
Bibliographic record
Abstract
We have directly measured the energy threshold and efficiency for bubble nucleation from iodine recoils in a ${\mathrm{CF}}_{3}\mathrm{I}$ bubble chamber in the energy range of interest for a dark matter search. These interactions cannot be probed by standard neutron calibration methods, so we develop a new technique by observing the elastic scattering of $12\text{ }\text{ }\mathrm{GeV}/c$ negative pions. The pions are tracked with a silicon pixel telescope and the reconstructed scattering angle provides a measure of the nuclear recoil kinetic energy. The bubble chamber was operated with a nominal threshold of $(13.6\ifmmode\pm\else\textpm\fi{}0.6)\text{ }\text{ }\mathrm{keV}$. Interpretation of the results depends on the response to fluorine and carbon recoils, but in general we find agreement with the predictions of the classical bubble-nucleation theory. This measurement confirms the applicability of ${\mathrm{CF}}_{3}\mathrm{I}$ as a target for spin-independent dark matter interactions and represents a novel technique for calibration of superheated fluid detectors.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".