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Diamond Particle Detectors for High Energy Physics

2016· article· en· W2421654670 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

VenueNuclear and Particle Physics Proceedings · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLarge Hadron ColliderDiamondDetectorPhysicsTracking (education)Interaction pointRadiation hardeningParticle physicsParticle detectorAtlas (anatomy)LuminosityOptoelectronicsOpticsNuclear physicsAstronomyMaterials science

Abstract

fetched live from OpenAlex

Diamond devices have now become ubiquitous in the LHC experiments, finding applications in beam background monitoring and luminosity measuring systems. This sensor material is now maturing to the point that the large pads in existing diamond detectors are being replaced by highly granular tracking devices, in both pixel and strip configurations, for detector systems that will be used in Run II at the LHC and beyond. The RD42 collaboration has continued to seek out additional diamond manufacturers and quantify the limits of the radiation tolerance of this material. The ATLAS experiment has recently installed, and is now commissioning a fully-fledged pixel tracking detector system based on diamond sensors. Finally, RD42 has recently demonstrated the viability of 3D biased diamond sensors that can be operated at very low voltages with full charge collection. These proceedings describe all of these advances.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.646

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 communication0.0000.001
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 head0.014
GPT teacher head0.215
Teacher spread0.201 · 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