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Record W3179750663 · doi:10.29303/jppipa.v7i3.716

Numerical Solution of Radioactive Core Decay Activity Rate of Actinium Series Using Matrix Algebra Method

2021· article· en· W3179750663 on OpenAlexaboutno aff
Anita Puji Pratiwi, Trapsilo Prihandono, Sri Handono Budi Prastowo

Bibliographic record

VenueJurnal Penelitian Pendidikan IPA · 2021
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsnot available
Fundersnot available
KeywordsNuclideDecay chainRadioactive decaySeries (stratigraphy)PhysicsNuclear physicsChemistryRadiochemistryGeology

Abstract

fetched live from OpenAlex

The Actinium 235 series is one of the radioactive series which is widely used as a raw material for reactors and nuclear activities. The existence of this series is found in several countries such as West USA, Canada, Australia, South Africa, Russia, and Zaire. The purpose of this study was to determine the activity value and the number of radioactive nucleus decay atoms on the actinium 235 rendered in a very long decay time of 4.3 x 109 years. The decay count in this study uses an algebraic matrix method to simplify the chain decay solution, which generally uses the concept of differential equations. The solution using this method can be computationally simulated using the Matlab program. This study indicates that the value of the decay activity experienced by each element in this series is the same, which is equal to 2,636 x 1011 Bq. This condition causes the actinium 235 series to experience secular equilibrium because the half-life of the parent nuclide is greater than the nuclide derivatives. The decay activity of the radioactive nucleus under the actinium 235 series is strongly influenced by the half-life of the nuclides, the decay constants, and the number of atoms after decay

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.040
GPT teacher head0.336
Teacher spread0.296 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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