Coupling Centrifuge Modeling and Laser Ablation Inductively Coupled Plasma Mass Spectrometry To Determine Contaminant Retardation in Clays
Bibliographic record
Abstract
Quantifying the retardation (Rd) of reactive solutes as they migrate through low-permeability clay-rich media is difficult, thus motivating this study to assess the viability of combining centrifuge modeling and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) techniques. An influent solution containing Cl-, trace metals, and lanthanide species flowed at 1.0 mL x h(-1) through an undisturbed clay-rich core sample (33 mm diameter x 50 mm long) mounted in a UFA Beckman centrifuge operating at 3000 rpm (N factor = 876 g). During the 87 day experiment the hydraulic conductivity of the core was 3.4 x 10(-10) m x s(-1). Effluent breakthrough data indicate the Rd of Tl to be 10; incomplete breakthrough (non-steady-state) data for 145Nd and 171Yb suggest Rd values of >>75 and >>85, respectively. At the completion of the transport experiment, longitudinal sections of the core solid were analyzed for 145Nd and 171Yb using a Cetac laser ablation system coupled with an ICP-MS. The longitudinal core sections yielded Rd values of >10000 for 145Nd and 171Yb. This study demonstrates coupling these techniques can provide Rd values for a wide range of reactive solutes with relatively rapid testing of small-scale, low hydraulic conductivity core samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".