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Record W2067551126 · doi:10.1063/1.1834705

A compact and portable PC-based Gundestrup–Langmuir probe diagnostic system

2004· article· en· W2067551126 on OpenAlexaffabout
P. Sicard, C. Boucher, A. Litnovsky, J.-P. St-Germain

Bibliographic record

VenueReview of Scientific Instruments · 2004
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsLangmuir probeData acquisitionLaptopComputer scienceRange (aeronautics)LangmuirMaterials sciencePhysicsComputer hardwarePlasma diagnosticsPlasmaNuclear physicsChemistryOperating system

Abstract

fetched live from OpenAlex

A compact Gundestrup–Langmuir probe diagnostics system capable of data acquisition as well as data analysis was conceived at INRS-EMT, Canada, and used at IPP-FZJ, Germany. Data acquisition and analysis can be done with this system using several types of probes (Langmuir, double-Langmuir, Mach, Gundestrup,…). The versatility as to the different types of probe that one can use and the relative small size of the whole system makes it advantageous. Using a laptop computer makes the system small size and highly portable. The system acquires data at 1000scans∕s at 12bit resolution on two probe systems simultaneously, using a total of 12 input channels. Bias is done by a DAC-ADC card and is amplified to give a ±100V sweeping range. Measured temperatures ranged from 0.75eVto6.0eV with densities observed as low as 1×1010cm−3 up to 5×1011cm−3, which are the range of conditions to be found in our experimental device. This system is also easy to reproduce since the hardware is commercially available and the scripts can be duplicated and modified according to the specifics of the hardware.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.484

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 communication0.0000.000
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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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 designSystematic review
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

Citations3
Published2004
Admission routes2
Has abstractyes

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