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Record W4399058828 · doi:10.31661/jbpe.v0i0.2405-1764

Survival by Selection: The Role of Natural Selection in Developing Biological Radiation Defenses

2024· article· en· W4399058828 on OpenAlex
Seyed Alireza Mortazavi, Ilham Said‐Salman, Sami El Khatib, Parmis Taghizadeh, Seyed Mohammad Javad Mortazavi, Lembit Sihver

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Biomedical Physics and Engineering · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsNatural selectionSelection (genetic algorithm)BiologyNatural (archaeology)Relevance (law)Evolutionary biologyEcologyComputational biologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Natural selection, a cornerstone of evolutionary biology, shapes the adaptations organisms develop to survive environmental pressures. This paper explores how natural selection drives biological adaptations to radiation exposure. We examine the genetic mechanisms at play, exemplified by the enhanced DNA repair capabilities observed in bacteria like Escherichia coli (E. coli) following exposure to radiation. We then investigate adaptations in humans residing in high-background radiation areas, highlighting potential genetic variations for radiation resistance. Finally, the contemporary relevance of natural selection is discussed, emphasizing its role in the emergence of antibiotic-resistant bacteria and the need for sustainable medical practices. By studying these adaptations, we gain a deeper understanding of evolution and its implications for medicine, conservation, and our overall understanding of life.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.163

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 head0.005
GPT teacher head0.212
Teacher spread0.207 · 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