Diffusive-Convective Mass Transfer Rates for Solutes Present on Both Sides of a Dialyzer Membrane
Bibliographic record
Abstract
The transport (J) of waste products across dialyzer membranes is known to be proportional to the blood inlet concentration (Cbi) according to J = KCbi, where K is the clearance. For solutes present on both sides of the membrane, like sodium chloride, it has been shown that under certain conditions the transport rate will depend linearly also upon the dialysis fluid inlet concentration Cdi according to J = KbCbi -KdCdi. Kb and Kd are generalized clearances, which depend upon flow rates and membrane permeability but are independent of the concentrations. We have extended the results of Ross et al. in three ways. First, they only considered ultrafiltration (UF) that is equally distributed along the dialyzer. This is an unrealistic assumption, especially in hemodiafiltration and hemofiltration treatments with large UF rates (Quf) leading to large pressure drops along the dialyzer. Our approach allows for an arbitrary UF distribution. Second, it was possible to incorporate the more realistic model of Villaroel et al. for the local combination of diffusion and convection. Finally, we allow an arbitrary distribution of blood among the different fibers. All of these results are valid in both cocurrent and countercurrent configurations. With a sieving coefficient of 1, a good approximation for small solutes, we were also able to show that Kd = Kb - Quf, irrespective of the UF distribution along the dialyzer. This is an important result that, for example, provides a theoretical foundation for allowing a nonzero Quf in conductivity based clearance measurements.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".