Bibliographic record
Abstract
The LHC neutrino experiments, FASER and SND@LHC were approved by the CERN Research Board in 2019 and 2021, respectively, to operate during LHC Run 3. Both experiments began taking physics data in July 2022 and have since recorded approximately 70 fb-1 of data from proton-proton collisions with a center-of-mass energy of 13.6 TeV. These experiments achieved the first direct observation of neutrino interactions at the LHC, using the active electronic components of their detector. Additionally, FASERν, using 2% of its data sample, detected the highest-energy νe and νµ interactions ever observed from an artificial source and made the first measurements of neutrino interaction cross-sections over energy ranges of 560–1740 GeV for νe and 520–1760 GeV for νµ. Additionally, both experiments are actively searching for physics beyond the Standard Model, with FASER already publishing initial results on Dark Photons and Axion-like Particles. In this report, we will discuss the status of the experiments, including the detector concept, performance, and the first physics results from Run 3 data.
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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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.011 |
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".