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SND@LHC: the scattering and neutrino detector at the LHC

2024· article· en· W3164567970 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Instrumentation · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsInstitute of Particle Physics
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekInstitut Català de Nanociència i NanotecnologiaAgencia Nacional de Investigación y DesarrolloCompagnia di San Paolo
KeywordsPhysicsLarge Hadron ColliderNeutrinoDetectorNuclear physicsCalorimeter (particle physics)Particle physicsMuonInteraction pointOptics

Abstract

fetched live from OpenAlex

Abstract SND@LHC is a compact and stand-alone experiment designed to perform measurements with neutrinos produced at the LHC in the pseudo-rapidity region of 7.2 < η < 8.4. The experiment is located 480 m downstream of the ATLAS interaction point, in the TI18 tunnel. The detector is composed of a hybrid system based on an 830 kg target made of tungsten plates, interleaved with emulsion and electronic trackers, also acting as an electromagnetic calorimeter, and followed by a hadronic calorimeter and a muon identification system. The detector is able to distinguish interactions of all three neutrino flavours, which allows probing the physics of heavy flavour production at the LHC in the very forward region. This region is of particular interest for future circular colliders and for very high energy astrophysical neutrino experiments. The detector is also able to search for the scattering of Feebly Interacting Particles. In its first phase, the detector is ready to operate throughout LHC Run 3 and collect a total of 250 fb -1 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.131

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.266
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it