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Record W2613249740

Simulations of GRETINA: Photopeak Efficiencies

2016· article· en· W2613249740 on OpenAlexaboutno aff
Leah Jarvis

Bibliographic record

VenueDigital Commons - Ursinus (Ursinus College) · 2016
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

We tested and improved upon computer simulations of the GRETINA gamma ray tracking array that is used to study the structure and properties of atomic nuclei at several national laboratories. As part of this work, it was necessary to assess photopeak efficiencies, the probability that the full energy of a gamma ray is collected, in order to fully understand and utilize experimental data. We developed a method to determine the thickness of the ‘dead layer’ of the back surface of the crystal by comparing measured photopeak efficiencies involving the back layer of segments with simulations. Because GRETINA contains two types of crystals with slightly different geometries, we also studied the relative photopeak efficiencies of the two crystal types. The purpose of our work was to validate the models used in the simulation code against radioactive source measurements. The finished product of this research will be reported at the fall meeting of the Division of Nuclear Physics of the American Physical Society in Vancouver, BC, this October.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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