Iodine Behavior Under Conditions Relating to Nuclear Reactor Accidents
Bibliographic record
Abstract
The short-term radiological impact of some serious reactor accidents may be governed by the release of airborne radioiodine to the environment. The impacts of parameters affecting iodine volatility, including radiation, iodine concentration, and solution pH, were investigated under a range of postaccident chemical conditions expected in a reactor containment structure. A bench-scale apparatus, installed in the irradiation chamber of a Gammacell, was used to measure the rate of iodine volatilization from dilute, 10-6 to 10-4 M, CsI solutions with pH values from 5 to 9. Iodine volatilization dramatically increased in the presence of radiation. The volatilization rates were nearly proportional to iodine concentration over the range of concentrations and pH values examined. Volatilization rate increased significantly with a decrease in pH. A kinetic-based model containing a mechanistic description of iodine chemistry was developed to simulate the radiation chemistry of iodine. The majority of the model prediction and experimental results of iodine volatilization rates were in agreement, although some divergence was evident.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".