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Record W4402969405 · doi:10.4103/rpe.rpe_25_24

News (IARP-YPG): Awards

2024· article· en· W4402969405 on OpenAlexaboutno aff
S. Anand

Bibliographic record

VenueRadiation Protection and Environment · 2024
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

The 16th International Congress of the International Radiation Protection Association (IRPA), with the theme of “Radiation Harmonization: Standing United for Protection,” took place in Orlando, Florida, from July 7 to 12, 2024, and was hosted by the Health Physics Society. One of the key highlights of the congress was the award for young radiation protection professionals by IRPA. This prestigious accolade aims to promote the advancement of radiation protection across all its fields and to recognize the outstanding contributions of young scientists and professionals. The award seeks to inspire the next generation of experts in radiation protection, encourage regional involvement, and reward dedication and excellence. Eligibility criteria for the award required candidates to be under 35 years of age with <10 years of experience in their respective fields. Candidates were also required to be officially nominated by an IRPA Associate Society, with each society permitted to nominate only one candidate. In addition, participants had to submit an abstract for an oral presentation at IRPA 16, along with a letter of recommendation, a CV, and a 1-min video summarizing their presentation’s key aspects. The IRPA 16 organizing committee appointed an esteemed Award Jury, chaired by Andrzej Wojcik of Stockholm University, a member of the IRPA 16 International Congress Programme Committee. The Jury evaluated the nominations and presentations, assessing the quality of the work, its significance to radiation protection, the quality of the abstract, and the effectiveness of the oral presentation. Fourteen young professionals from fourteen different countries were nominated by their respective societies, all vying for this esteemed recognition. On the final day of the congress, the award was presented to three outstanding candidates: Gabriel Dupont from France, Riya Dey from India, and Francesca Luoni from Italy [Figures 1 and 2].Figure 1: With Prof. Andrzej Wojcik and Dr. Bernard Le GuenFigure 2: Sharing the stage with all the award nomineesMs. Riya Dey, from the Health Physics Division, Bhabha Atomic Research Centre, was nominated by the Indian Association for Radiation Protection. Notably, she had previously received the IRPA Young Scientists Award at the AOCRP6 congress in Mumbai in 2023, through which the registration fee to attend the IRPA 16 congress was waived. In addition, her travel and accommodation expenses were covered by the Montreal Fund, courtesy of the IRPA 16 International Congress Support Committee. In the “Numerical and Computational Dosimetry” session, Ms. Dey presented her paper titled “Particle Deposition in Human Upper Airways and Trachea,” coauthored with Hemant K. Patni, M. S. Kulkarni, and S. Anand. Her research focused on the risks posed by inhaling radioactive aerosols at concentrations exceeding safe limits, which can lead to harmful exposure to the lungs and adjacent organs. The study analyzed the effects of complex respiratory tract geometry on particle deposition profiles. Using the ICRP-145 dataset, the male respiratory geometry, including the upper airways and trachea, was converted into a step file for use in Computational Fluid and Particle Dynamics simulations. The simulations explored fluid flow profiles and particle deposition patterns within this intricate respiratory system, shedding light on the mechanisms of inertial impaction, Brownian diffusion, and gravitational settling. The outcomes of this research can be integrated with Monte Carlo-based codes and voxel/hybrid mesh phantom geometry to estimate the inhalation dose from deposited radioactive particles. Her work is instrumental in improving our understanding of nonuniform particle deposition within the airways and has significant implications for realistic dose estimation. In recognition of her exceptional work and presentation, Ms. Riya Dey was awarded the IRPA 16 Silver Award, securing second place. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.061
GPT teacher head0.343
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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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