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Record W2128550387 · doi:10.1139/cjp-2015-0372

Self-absorption coefficients of sulfur emission lines

2015· article· en· W2128550387 on OpenAlexvenueno aff
A.A.M. Habib, M.M. Aish

Bibliographic record

VenueCanadian Journal of Physics · 2015
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsnot available
Fundersnot available
KeywordsPlasmaPhysicsAtomic physicsVoigt profileAbsorption (acoustics)Line (geometry)Plasma parametersSpectral lineEmission spectrumSpectroscopyAbsorption spectroscopySpectral line shapePhotonLaserOpticsNuclear physics

Abstract

fetched live from OpenAlex

A theoretical approach is developed to calculate the mean probability of photon capture for the resonance lines emitted by a neutral sulfur atom in the vacuum ultraviolet spectral region in the case of a thermal plasma mixture. The calculations are to estimate the self-absorption effect in a quantitative way assuming a Voigt line profile. The variation of the probability of photon capture with the temperature, the SF6 proportions in SF6-N2 thermal plasma mixture, and the size of the plasma are considered. The results obtained may be of practical importance in plasma modeling and plasma diagnostics. They may also be applied to find out self-absorption-free emission lines appropriate for laser-induced breakdown spectroscopy experiments used for analytical purposes because of their simplicity. Influence of three parameters (temperature, plasma size, and SF6 proportion) on the probability of photon capture has been studied using a Voigt line profile.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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