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Record W2588189430

Dark Matter, Supersymmetry and the ATLAS Detector

2017· article· en· W2588189430 on OpenAlexaboutno aff
Sheetal Saxena

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsDark matterAtlas (anatomy)Atlas detectorPhysicsParticle physicsSupersymmetryAstronomyLarge Hadron ColliderGeologyPaleontology
DOInot available

Abstract

fetched live from OpenAlex

Masters Report Univer sity of Toronto Department of Physics August 21, 2008 A Study of Jet and Missing Transv erse Ener gy Reconstruction and Data Cleaning Techniques on ATLAS Calorimeter Cosmic Ray Data Travis Bain 995981834 Abstract Monte Carlo generated QCD jets, and jets reconstructed from cosmic ray data are analyzed and compared. This comparison allo ws some of the rst opportunities to run through a full study , from data collection, to reconstruction, to analysis, within ATLAS, using real events. The ability to handle data at every step of the way will be crucial in achie ving a ìsteady-stateî mode of operation in the coming months and years of ATLAS operation. The use of electromagnetic fractions as a data cleaning technique within the ATLAS calorimeter system is also studied and sho wn to be a rob ust tool in remo ving high ener gy cosmic ray events as a background from jet and E Miss T distrib utions

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.016
GPT teacher head0.251
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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