Colloid-Facilitated Cs Transport through Water-Saturated Hanford Sediment and Ottawa Sand
Bibliographic record
Abstract
In this study, a series of saturated column experiments were conducted to investigate effects of colloids on Cs transport in two types of porous media (Hanford sediment characteristic of 2:1 clay minerals and silica Ottawa sand). The colloids used were obtained by reacting Hanford sediment with simulated tank waste solutions. Because of the highly nonlinear nature of Cs sorption found in batch experiments, we used two different concentrations of Cs (7.5 x 10(-5) M and 1.4 x 10(-8) M) for the transport experiments. The presence of colloids facilitated the transport of Cs through both Hanford sediment and Ottawa sand via association of Cs with mobile colloidal particles. Due to the nonlinearity of the Cs sorption, the colloid-facilitated Cs transportwas more pronounced atthe low Cs concentration (1.4 x 10(-8) M) than at the high concentration (7.5 x 10(-5) M) when expressed relative to the inflow Cs concentration. In the absence of colloids, no Cs moved through the 10-cm long columns during the experiment within about 20 pore volumes, exceptfor the high Cs concentration in the Ottawa sand where a complete Cs breakthrough was obtained. Also, it was found that colloid-associated Cs could be partially stripped off from colloids during the transport. The stripping effect was controlled by both Cs concentration and sorption capacity of the transport matrix.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".