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Record W2254303959 · doi:10.2172/1157316

Tracking Tests for the SNS Fast Injection Bump Power Supply

2004· report· en· W2254303959 on OpenAlexaff
W. Eng, R. Lambiase, Y. Lee, W. McGahern, C. Pai, J. Sandberg, Jordan Smith, A. Soukas, Jin Wei, Binbin Weng

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of Toronto
FundersArgonne National LaboratoryUT-BattelleBattelleU.S. Department of Energy
KeywordsPower (physics)Construct (python library)Tracking (education)Computer scienceWaveformReal-time computingComputer hardwareElectrical engineeringDatabaseEmbedded systemEngineeringTelecommunicationsPhysicsProgramming language

Abstract

fetched live from OpenAlex

The tracking requirement of the SNS Fast Injection Bump power supplies is described. In addition to the usual tracking between the load current and the input reference of a power supply, these power supplies must also track between pairs of units under slightly different loads. This paper describes the use of a current-null test to measure tracking performances. For the actual tests, a single dummy magnet load was used to measure the tracking between the first two production units at the manufacturer’s facility. Using the Yokogawa WE7000 PC-based measurement instrument, input and output waveforms are digitized and stored in data files. A program written for this application is then used to extract data from these files to construct, analyze the waveforms and characterize the power supply performance. Results of the measurements of two SNS Fast Injection Bump power supplies will be presented in this paper.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.305
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.044
GPT teacher head0.323
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations2
Published2004
Admission routes1
Has abstractyes

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