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Record W2105391387

Gaseous by-products from ARGON thermal plasma-air-water system

2008· article· en· W2105391387 on OpenAlexaff
Péricles Inácio Khalaf, Nito Ângelo Debacher, M.H. Majles Ara, J.S. Chang

Bibliographic record

VenueInternational Conference on Gas Discharges and Their Applications · 2008
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsArgonPlasma torchPlasmaNOxTorchVolumetric flow rateNonthermal plasmaAnalytical Chemistry (journal)ChemistryOxygenMaterials scienceEnvironmental chemistryCombustionThermodynamicsMetallurgy
DOInot available

Abstract

fetched live from OpenAlex

In this work, toxic gaseous by-products such as CO, NO, NO2, etc., generated by an argon plasma torch in different air environments were experimentally investigated. Experiments were conducted for plasma torch power from 0 to 1.5 kW, argon plasma flow rate from 0 to 20 L.min-1, and oxygen concentration from 0 to 12 %. In air, a significant amount of toxic gaseous by-products were observed. However, in the Ar-air-water system, the presence of water reduced NOx (sum of NO and NO2 concentrations) and CO formation. The mean plasma jet electron temperature value was measured by optical emission spectroscopy. The averaged axial temperature slightly increased with the increase of the argon flow rate.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.588

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 head0.028
GPT teacher head0.248
Teacher spread0.220 · 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 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
Published2008
Admission routes1
Has abstractyes

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