MétaCan
Menu
Back to cohort
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 OpenAlexaff
Seyed Alireza Mortazavi, Ilham Said‐Salman, Sami El Khatib, Parmis Taghizadeh, Seyed Mohammad Javad Mortazavi, Lembit Sihver

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.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Explore more

Same venueJournal of Biomedical Physics and EngineeringSame topicDNA Repair MechanismsFrench-language works237,207