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Record W4400672890 · doi:10.1088/1402-4896/ad640a

Calculation of electron-impact ionization of various benzene derivatives

2024· article· en· W4400672890 on OpenAlexafffund
Anirudh Krishnadas, Nidhi Sinha, Tom Kirchner, Bobby Antony

Bibliographic record

VenuePhysica Scripta · 2024
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectron ionizationBenzeneIonizationElectronAtomic physicsMaterials scienceComputational physicsPhysicsNuclear physicsIonChemistryQuantum mechanicsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Calculations of the electron-impact ionization cross-section of pyrene, anthracene, benzoyl chloride, benzophenone, and phthalonitrile are reported over a wide energy range. A comparison of theoretical models, viz. spherical complex optical potential (SCOP), pixel counting method (PCM), and the binary encounter Bethe (BEB) model is carried out. SCOP calculations provide the inelastic cross-section, and the ionization cross-section is extracted from it. This result is modified with PCM, a model previously applied to ion collisions which takes geometric screening corrections into account. The BEB model is used as an independent approach to calculate the ionization cross-section. It is demonstrated that all model results are in reasonable agreement with each other. Comparison is also made with other theoretical data where available.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.289
Teacher spread0.277 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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