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Record W2054865492 · doi:10.1134/s1063780x13030069

Measurements of the electron density and degree of plasma ionization in a plasma target based on a linear electric discharge in hydrogen

2013· article· en· W2054865492 on OpenAlexaff
А. П. Кузнецов, O. A. Byalkovskii, R. O. Gavrilin, А. А. Голубев, K. L. Gubskii, I. V. Rudskoi, S. Savin, V. I. Turtikov, A. V. Khudomyasov

Bibliographic record

VenuePlasma Physics Reports · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsIonizationPlasmaAtomic physicsHydrogenElectronElectron densityMaterials scienceRange (aeronautics)Plasma parametersIonPhysicsNuclear physics

Abstract

fetched live from OpenAlex

Laser interferometry methods were used to measure the density of free electrons and degree of plasma ionization in a hydrogen target intended for experiments on determining energy losses of heavy ion beams in an ionized matter. It is shown that the linear electron density can be varied in the range from 3.3 × 10 17 to 1.3 × 10 18 cm −2 by varying the initial plasma parameters (the hydrogen pressure in the target and the discharge current). The error in measuring the linear electron density in the entire range of the varied plasma parameters was less than 1%. The maximum degree of plasma ionization achieved at the initial gas pressure of 1 mbar was 0.62 ± 0.05.

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)0.000
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.231
Teacher spread0.215 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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