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Record W2551761505 · doi:10.1002/ppap.201600191

Energetics of reactions in a dielectric barrier discharge with argon carrier gas: V hydrocarbons

2016· article· en· W2551761505 on OpenAlex
Bernard Nisol, Sean Watson, Sophie Lerouge, M. R. Wertheimer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePlasma Processes and Polymers · 2016
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsÉcole de Technologie SupérieureCentre Hospitalier de l’Université de MontréalPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDielectric barrier dischargeArgonMonomerPlasma polymerizationAtmospheric pressurePlasmaReagentDielectricMoleculePolymerizationChemistryAnalytical Chemistry (journal)HydrocarbonFluorinePhotochemistryMaterials scienceOrganic chemistryPolymerOptoelectronics

Abstract

fetched live from OpenAlex

We report dielectric barrier discharge (DBD)‐based atmospheric pressure (AP) plasma polymerization (PP) experiments using argon carrier gas and a wide variety of hydrocarbon molecules as the precursors (“monomers”). As in our preceding research with other reagents, unprecedented precision and reproducibility in energy measurements is again demonstrated. Measurements based on various aliphatic and aromatic hydrocarbon compounds have yielded values of E m , the energy absorbed from the plasma by each monomer molecule. Systematic differences among families of compounds enabled us to draw several important conclusions about fragmentation and polymerization in the DBD plasma environment, observations which are in fair qualitative agreement with low‐pressure radio‐frequency PP data by Yasuda and Hirotsu from the 1970s.

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.

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 score0.488
Threshold uncertainty score0.321

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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