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Record W3161955591 · doi:10.1080/09553002.2021.1931529

Women’s contributions to radiobiology in Ireland; from small beginnings….

2021· article· en· W3161955591 on OpenAlexaff
Orla Howe, Fiona M. Lyng, Carmel Mothersill

Bibliographic record

VenueInternational Journal of Radiation Biology · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicTwentieth Century Scientific Developments
Canadian institutionsMcMaster University
FundersScience Foundation Ireland
KeywordsRadiobiologyTranslational researchLow Dose RadiationPreclinical researchMedicineLibrary scienceMedical physicsPathologyRadiation therapyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe the contribution of women radiobiologists in Ireland to the development of the discipline internationally and at home and to discuss the history of radiobiology in Ireland to date. This parallels the history of the evolution of a small radiobiology group in Kevin Street, Dublin Institute of Technology (DIT) which was formerly part of the City of Dublin Vocational Education Committee. There followed years of development first as a radiobiological research center which evolved in the FOCAS Research Institute now embedded within Technological University Dublin (TU Dublin). CONCLUSIONS: Over the last 45 years, the women of the Radiation and Environmental Science Centre (RESC) contributed to the major paradigm shift in low dose radiobiology contributing exciting new research concerning non-targeted effects, including discovery of lethal mutations, medium transfer bystander mechanisms, and signaling pathways. They also developed translational research using human explant culture systems with unique immunocytochemical methods and more recently evolved to molecular and spectroscopic analysis of clinical samples. The RESC also developed unique in vitro research methods into effects of radiation on non-human species of concern in ecosystems.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0070.003
Open science0.0010.010
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0140.004

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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.

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
Published2021
Admission routes1
Has abstractyes

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