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Record W4321597054 · doi:10.3390/atoms11030041

Charge-State Distributions after Beta Decay of 6He to Form 6Li+

2023· article· en· W4321597054 on OpenAlexafffund
Aaron Bondy, G. W. F. Drake

Bibliographic record

VenueAtoms · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsPhysicsIonizationAtomic physicsCharge (physics)BETA (programming language)Range (aeronautics)Work (physics)State (computer science)Energy (signal processing)IonQuantum mechanicsAlgorithmMaterials science

Abstract

fetched live from OpenAlex

The shake-off processes and charge-state fractions of 6Li+, 6Li++, and 6Li3+ were studied following the beta decay of 6He in the 1s21S0, 1s2s1S0, and 1s2s3S1 initial states. The sudden approximation was used, together with fully correlated Hylleraas wave functions and pseudostates. A projection operator method was introduced to separate the charge-state fractions in the positive energy region of overlapping continua. The results show that 6Li++ (single-ionisation) remains dominant, even in the energy range E>0, where the formation of 6Li3+ (double-ionisation) is energetically allowed. The results reduce disagreements with the experiment for the fraction of 6Li3+ by nearly an order of magnitude, but substantial disagreements remain that are inconsistent with the sudden approximation widely used in other similar work.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.294
Teacher spread0.279 · 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
Published2023
Admission routes2
Has abstractyes

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