MétaCan
Menu
Back to cohort
Record W2038307966 · doi:10.1088/0031-9155/56/12/012

Development and characterization of an<i>in vitro</i>alpha radiation exposure system

2011· article· en· W2038307966 on OpenAlexaff
Lindsay A. Beaton-Green, Trevor A Burn, Trevor J. Stocki, Vinita Chauhan, Ruth C. Wilkins

Bibliographic record

VenuePhysics in Medicine and Biology · 2011
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsHealth CanadaCarleton University
Fundersnot available
KeywordsAlpha particleLinear energy transferRelative biological effectivenessDosimetryMicrobeamMonte Carlo methodRadiationAlpha (finance)Nuclear medicinePhysicsMaterials scienceRadiochemistryOpticsChemistryNuclear physicsMathematicsStatisticsMedicine

Abstract

fetched live from OpenAlex

A simple in vitro alpha radiation exposure system (ARES) was designed to study the biological effects of alpha particle radiation. The ARES consists of six (241)Am electroplated stainless steel discs with activities averaging 66 kBq and Mylar-based culture dishes to allow the transmission of alpha particles. The dosimetry of the exposure system was calculated using the GEANT4 Monte Carlo simulation toolkit with the source code adapted from the open-source Microbeam example. The average dose rate and linear energy transfer of the system was simulated to be 0.98 ± 0.01 (statistical)(+0.18)( - 0.00) (systematic) Gy h(-1) and 127.4 ± 0.4 (statistical)(+23)( - 0) (systematic) keV µm(-1), respectively. The system was characterized by a comparison of the survival curves of gamma and alpha irradiated cell lines which showed a relative biological effectiveness of 6.3. This is in good agreement with values obtained using other published alpha particle exposure systems. Results show that the ARES provides a simple, cost-effective exposure platform for research into the biological effects of alpha particle radiation using in vitro modelling of cell cultures.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.202

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 head0.108
GPT teacher head0.322
Teacher spread0.214 · 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 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

Citations20
Published2011
Admission routes1
Has abstractyes

Explore more

Same venuePhysics in Medicine and BiologySame topicRadiation Therapy and DosimetryFrench-language works237,207