Experimental factors and their impact on understanding corrosion in anoxic environments
Bibliographic record
Abstract
Abstract The long‐term disposal of nuclear waste in deep geological repositories requires safe containment for up to one million years. To understand how the waste will respond to the gradually evolving environment, researchers can perform sensitive experiments in the laboratory to replicate the repository conditions at specific time points. In Belgium, spent nuclear fuel will be housed within a carbon steel overpack, which is encased within a cement buffer, which may include a stainless steel liner (the “envelope”). The range of corrosion behaviors for carbon steel, and to a lesser extent, stainless steel, has been studied through hydrogen evolution, an end‐product of oxidation under repository conditions. Considerable time may be required for metallic surfaces to approach a steady hydrogen evolution and this is dependent upon the starting condition of the specimen surfaces. The use of nominally‐similar materials can result in significant variation in the reported corrosion rates. The presence of cements, which generate their own hydrogen and influence water chemistry as a function of time, add complexity to even simple experimental configurations that requires careful interpretation.
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 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) | 0.001 | 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 teacher head, 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".