Dust-induced beam losses in the Large Hadron Collider
Bibliographic record
Abstract
Since the start of the Large Hadron Collider (LHC), dust-induced beam loss events resulted in more than hundred premature beam aborts and more than ten dipole quenches during proton physics operation. The events are presumably caused by micrometer-sized dust grains, which are attracted by the proton beams and consequently give rise to beam losses due to inelastic proton-nucleus collisions. Besides the events which trigger dumps or quenches, a large number of smaller dust events has been detected by the beam loss monitors every year. Although these events are not detrimental for physics operation, they are still carefully scrutinized as they give a better understanding about the correlation with beam parameters, about the long-term evolution of event rates, and about possible correlations with shutdown activities and the installation of new equipment. In this contribution, we present a summary of observations from the first three runs of the LHC.
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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 | 0.000 | 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 | 0.000 | 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 | 0.001 |
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 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".