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Record W4293498763 · doi:10.1088/1751-8121/ac8a2b

Atomic excitation caused by α decay of the nucleus: model study

2022· article· en· W4293498763 on OpenAlexafffund
Ian Breukelaar, W. van Dijk

Bibliographic record

VenueJournal of Physics A Mathematical and Theoretical · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsRedeemer UniversityMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIonizationSchematicAtomic physicsElectronAtom (system on chip)PhysicsPoint particleExcitationStatistical physicsNuclear physicsQuantum mechanicsIonComputer scienceElectronic engineering

Abstract

fetched live from OpenAlex

Abstract When the nucleus of an atom decays by emitting an α particle, the surrounding electrons are disturbed and the atom may be ionized. Practically all calculations so far done for this ionization process are based on Migdal’s method in which the α particle is treated as a classical point charge that is emitted by the nucleus at a certain time. Migdal’s method yields the ionization probability that is in reasonable agreement with experiment. On the other hand, Kataoka et al indicated by means of a schematic model calculation that a fully quantum mechanical treatment of the α particle leads to the ionization probability much smaller than the one predicted by Migdal’s method. We reexamine Kataoka et al’s calculation by simplifying the model of the atom such that an exact calculation is feasible. We find that Migdal’s method can be approximately justified, and clarify the earlier analysis.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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 designSimulation or modeling
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
Published2022
Admission routes2
Has abstractyes

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