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Record W2994919087 · doi:10.1103/physreva.82.062701

Reaction dynamics in double ionization of helium by electron impact

2010· article· en· W2994919087 on OpenAlexfundno aff
Marcelo F. Ciappina, Michael Schulz, Tom Kirchner

Bibliographic record

VenuePhysical Review A · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsDouble ionizationPhysicsElectron ionizationIonizationAtomic physicsHeliumMonte Carlo methodIonElectronImpact ionizationWork (physics)Generator (circuit theory)Nuclear physicsQuantum mechanicsPower (physics)

Abstract

fetched live from OpenAlex

We present theoretical fully differential cross sections (FDCS) for double ionization of helium by $500$ eV and $2$ keV electron impact. Contributions from various reaction mechanisms to the FDCS were calculated separately and compared to experimental data. Our theoretical methods are based on the first Born approximation. Higher-order effects are incorporated using the Monte Carlo event generator technique. Earlier, we successfully applied this approach to double ionization by ion impact, and in the work reported here it is extended to electron impact. We demonstrate that at $500$ eV impact energy, double ionization is dominated by higher-order mechanisms. Even at $2$ keV, double ionization does not predominantly proceed through a pure first-order process.

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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.004
GPT teacher head0.299
Teacher spread0.295 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

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