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Low Doses of Radiation Reduce Risk <i>in Vivo</i>

2007· article· en· W2061598557 on OpenAlex

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

VenueDose-Response · 2007
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsIn vivoIonizing radiationLow Dose RadiationCancerMedicineToxicologyNuclear medicineIrradiationPhysiologyBiologyInternal medicineGeneticsPhysics

Abstract

fetched live from OpenAlex

The "Linear No Threshold" hypothesis, used in all radiation protection practices, assumes that all doses, no matter how low, increase the risk of cancer, birth defects and heritable mutations. In vitro cell based experiments show adaptive processes in response to low doses and dose rates of low LET radiation, and do not support the hypothesis. This talk will present cellular data and data from animal experiments that test the hypothesis in vivo for cancer risk. The data show that a single, low, whole body dose (less than about 100 mGy) of low LET radiation, given at low dose rate, increased cancer latency and consequently reduced both spontaneous and radiation-induced cancer risk in both genetically normal and cancer-prone mice. This adaptive response lasted for the entire lifespan of all the animals that developed these tumors, and effectively restored a portion of the life that would have been lost due to the cancer in the absence of the low dose. Overall, the results demonstrate that the assumption of a linear increase in risk with increasing dose in vivo is not warranted, and that low doses actually reduce risk.

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)0.004
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.288
Teacher spread0.281 · 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