Preliminary importance analyses on model for pH in the presence of organic impurities in the aqueous phase for a severe accident of a nuclear power plant
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.
Bibliographic record
Abstract
In this paper, a model is developed for calculating pH in the presence of organic impurities due to dissolution of paint and/or continuous injection of organic impurities in the sump. The model is implemented in the AnCheBi code for the analysis of chemical behaviors of the iodine in the containment when the pH changes during a severe accident. Validation of the model is performed with P10T2 and P11T1 experiments carried out by AECL in Canada under the BIP project. Importance analyses of the pH calculation model in the AnCheBi code are then performed with the aforementioned experimental data via Latin hypercube sampling on the reaction coefficients, sensitivity analyses of AnCheBi, and calculation of the correlation coefficients between the reaction coefficients and figure of merits (the pH and the concentrations of the various iodine species). From the importance analyses, we provide the sensitivity of the pH calculation model to the change of pH and the concentrations of the various iodine species and the reaction coefficients related with the dominant phenomena underlying the change of pH and the concentrations of the species.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it