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Record W4388210851 · doi:10.1139/cjp-2023-0217

On the electron impact cross-section maxima for dissociative and non-dissociative single ionization of molecules and radicals

2023· article· en· W4388210851 on OpenAlexvenueno aff
A. C. F. Santos

Bibliographic record

VenueCanadian Journal of Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
FundersFinanciadora de Estudos e ProjetosFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsPolarizabilityAtomic physicsIonizationPhysicsElectron ionizationFragmentation (computing)ElectronMoleculeCross section (physics)IonNuclear physics

Abstract

fetched live from OpenAlex

Determining absolute electron impact ionization cross-sections for atoms and molecules, whether through experimental or theoretical means, poses a formidable challenge and is typically limited to a narrow selection of species. In this paper, by using measured cross-sections and polarizability data, it was obtained empirical scaling laws for total single ionization and non-dissociative single ionization cross-section maximum of neutral molecules by collisions with electrons. It is found that the total single ionization cross-sections scale linearly with the target electric static polarizability, while the non-dissociate cross-sections exhibit a saturation effect for large target polarizabilities. This saturation effect is interpreted as the increasing role of fragmentation with polarizability.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.267
Teacher spread0.257 · 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
Published2023
Admission routes1
Has abstractyes

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