Summary of Radiation Research Society Online 67th Annual Meeting, Symposium on “Radiation and Circulatory Effects”
Bibliographic record
Abstract
PURPOSE: Annual Meeting, October 3-6 2021. MATERIALS AND METHODS: Different epidemiological cohorts were analyzed with various statistical means common in epidemiology. The cohorts included the one from the U.S. Million Person Study and the Canadian Fluoroscopy Cohort Study. In addition, one of the contributions in our article relies on results from analyses of the Japanese atomic bomb survivors, Russian emergency and recovery workers and cohorts of nuclear workers. The Canadian Fluoroscopy Cohort Study data were analyzed with a larger series of linear and nonlinear dose-response models in addition to the linear no-threshold (LNT) model. RESULTS AND CONCLUSIONS: The talks in this symposium showed that low/moderate acute doses at low/moderate dose rates can be associated with an increased risk of CVD, although some of the epidemiological results for occupational cohorts are equivocal. The usually only limited availability of information on well-known risk factors for circulatory disease (e.g. smoking, obesity, hypertension, diabetes, physical activity) is an important limiting factor that may bias any observed association between radiation exposure and detrimental health outcome, especially at low doses. Additional follow-up and careful dosimetric and outcome assessment are necessary and more epidemiological and experimental research is required. Obtaining reliable information on other risk factors is especially important.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.117 | 0.052 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".