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Record W2993316561

Radioresistance: Implications for Astrobiological and Medical Research

2019· article· en· W2993316561 on OpenAlexaff
James J. Lai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicTardigrade Biology and Ecology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRadioresistanceDeinococcus radioduransAstrobiologyExtraterrestrial lifeDNA damageBiologyIonizing radiationRadiobiologyDNA repairComputational biologyDNAGeneticsRadiation therapyPhysicsMedicineIrradiation
DOInot available

Abstract

fetched live from OpenAlex

Ionizing radiation is commonly thought to be dangerous to, and even incompatible with, terrestrial life, due to its damaging effects on vital biomolecules like DNA. However, there exist organisms such as tardigrades, as well as several bacterial species, such as Deinococcus radiodurans, which have been observed to survive exposure to radiation levels in excess of 5000 Gy. This is accomplished by differing mechanisms, but in general involve processes to protect or rapidly repair molecules such as DNA that are damaged by the high-energy ionizing radiation. In this Letter to the iScientist, current understanding of the biology of radioresistant organisms is summarized. Subsequently, it is argued that furthering our understanding of these organisms and the mechanisms by which they withstand ionizing radiation have important applications for a variety of fields. These include applications to the astrobiological search for life beyond Earth, as understanding the potential limits of radioresistance may allow for the expansion or constraint of possible environments in which extraterrestrial life may survive, guiding future life detection efforts. At the same time, mechanisms of DNA repair in radioresistant organisms may provide avenues of exploration in the search for interventions that may be applied to addressing DNA damage in humans, a problem associated both with cancer and aging.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.059
GPT teacher head0.327
Teacher spread0.268 · 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.

Study designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

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