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Record W4393145523 · doi:10.1097/hp.0000000000001815

Saccharomyces Cerevisiae as a Model Organism for Retrospective Impedance Biodosimetry

2024· article· en· W4393145523 on OpenAlexaff
Amna Hassan, Kirk D. Atkinson

Bibliographic record

VenueHealth Physics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRadiation Effects and Dosimetry
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsBiodosimetryOrganismSaccharomyces cerevisiaeMicrobiologyBiologyYeastGeneticsIonizing radiationPhysicsIrradiationNuclear physics

Abstract

fetched live from OpenAlex

ABSTRACT: Previous studies have shown that measuring changes in electrical impedance that follow radiation-induced suppression of metabolic activity in irradiated yeast cells can be used to determine radiation dose. The current work investigates the radiation response of Saccharomyces cerevisiae cells by using metabolic activity of cells as a damage indicator. Impedance biodosimetry was examined as a method to evaluate the radiation response of yeast cells. Active lab-grade dry yeast cells were used as the biological material as these samples are simple to handle and have a long shelf-life. A novel dosimeter design has been developed with a strict fabrication method and measurement procedure to ensure reproducible measurements are possible. Prepared yeast samples were irradiated to doses from 0.5 to 8 Gy using a 137Cs source, and a dose response curve was developed that showed a linear relationship of dose with changes in impedance measurements. Fading of the impedance signal was also investigated, and it was shown that there was no noticeable fading of the impedance signal over a period of 7 mo. Finally, the lowest detectable limit measured using this methodology was determined to be 300 mGy. This work presents an alternative retrospective dosimetry technique that can be used at a high scale and low cost following large-scale radiological accidents.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.303
Teacher spread0.282 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2024
Admission routes1
Has abstractyes

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