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Record W2893778533 · doi:10.1080/09553002.2018.1511929

The influence of changing dose rate patterns from inhaled beta-gamma emitting radionuclide on lung cancer

2018· article· en· W2893778533 on OpenAlexafffund
Stephanie Puukila, Christopher Thome, Antone L. Brooks, Gayle E. Woloschak, Douglas R. Boreham

Bibliographic record

VenueInternational Journal of Radiation Biology · 2018
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsNOSM UniversityBruce Power (Canada)Laurentian University
FundersNational Cancer InstituteMitacsBruce Power
KeywordsBeagleRadionuclideInhalationMedicineLung cancerNuclear medicineLungDose rateInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

Purpose: Dose and dose rate are both appropriate for estimating risk from internally deposited radioactive materials. We investigated the role of dose rate on lung cancer induction in Beagle dogs following a single inhalation of strontium-90 (90Sr), cerium-144 (144Ce), yttrium-91 (91Y), or yttrium-90 (90Y). As retention of the radionuclide is dependent on biological clearance and physical half-life a representative quantity to describe this complex changing dose rate is needed.Materials and methods: Data were obtained from Beagle dog experiments from the Inhalation Toxicology Research Institute. The authors selected the dose rate at the effective half-life of each radionuclide (DRef).Results: Dogs exposed to DRef (1–100 Gy/day) died within the first year after exposure from acute lung disease. Dogs exposed at lower DRef (0.1–10 Gy/day) died of lung cancer. As DRef decreased further (<0.1 Gy/day 90Sr, <0.5 Gy/day 144Ce, <0.9 Gy/day 91Y, <8 Gy/day 90Y), survival and lung cancer frequency were not significantly different from control dogs.Conclusion: Radiation exposures resulting from inhalation of beta-gamma emitting radionuclides that decay at different rates based on their effective half-life, leading to different rates of decrease in dose rate and cumulative dose, is less effective in causing cancer than acute low linear energy transfer exposures of the lung.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.011
GPT teacher head0.334
Teacher spread0.322 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2018
Admission routes2
Has abstractyes

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