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Record W3035539746 · doi:10.1142/s2661339520500079

CERN Beamline for Schools 2017 Student Experiment: Search for Isolated Fractionally Charged Particles

2020· article· en· W3035539746 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Physics Educator · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
FundersUniversity of AlbertaCERN
KeywordsLarge Hadron ColliderBeamlinePhysicsSet (abstract data type)Nuclear physicsProtonParticle physicsBeam (structure)Computer scienceOpticsProgramming language

Abstract

fetched live from OpenAlex

This article was mainly written by a team of high school students that have won the CERN Beamline for Schools (BL4S) competition in 2017. They had some help from professional scientists, in particular Branislav Ristic. The team had proposed to set up an experiment to search for elementary particles with a fractional electric charge. This paper describes the preparation of their proposal, experimental setup, detectors and data analysis throughout the search for such particles using a 10[Formula: see text]GeV[Formula: see text][Formula: see text] proton beam with a fixed iron target. It was clear to the team that the chance for finding such particles in a relatively simple experiment was minimal but that by doing this experiment they would learn a lot about experimental physics. Due to large amounts of noise, the result of the experiment is inconclusive. Further experimentation to search for these hypothesized particle is encouraged.

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 score0.267
Threshold uncertainty score0.495

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 head0.058
GPT teacher head0.341
Teacher spread0.283 · 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