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Record W7034553950

Verification and Analysis Development for Proposed Bethe-Heitler Pair Production Asymmetry Experiment

2023· dissertation· en· W7034553950 on OpenAlexfundno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
FundersAlliance de recherche numérique du Canada
KeywordsAsymmetryField (mathematics)Production (economics)Component (thermodynamics)Work (physics)Development (topology)
DOInot available

Abstract

fetched live from OpenAlex

This thesis shows the simulated results of the proposed Bethe-Heitler Pair Production\nEnergy Asymmetry experiment. This asymmetry measurement is an emergent property of\nthe 2nd order cross-section of electron-positron pair production and therefore an important\nmeasure of higher order effects of the field theory. The simulated limits of the measurement\nare determined and reported as they would be relevant to the experimentalist. The analysis\nperformed on the simulated data was done using principal component analysis and linear\nregression of modified, non-linear data. The results as found by this work support the current\nexperiment design being capable of producing a cross-sectional asymmetry measurement but\nwith poor resolutions in both energy and angle calculations. Possible avenues to improve the\neffectiveness of the design are put forward and the methods of analysis are detailed such that\nany future design revisions can be reviewed efficiently.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.018
GPT teacher head0.199
Teacher spread0.182 · 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 designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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