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Record W57653626 · doi:10.13182/nt02-a3267

Iodine Behavior Under Conditions Relating to Nuclear Reactor Accidents

2002· article· en· W57653626 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

VenueNuclear Technology · 2002
Typearticle
Languageen
FieldChemistry
TopicRadioactive element chemistry and processing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIodineVolatilisationChemistryVolatility (finance)RadiochemistryEnvironmental chemistry

Abstract

fetched live from OpenAlex

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0210.001

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 head0.023
GPT teacher head0.267
Teacher spread0.243 · 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