DIFFUSIVE-CONVECTIVE MASS TRANSFER RATES FOR SOLUTES PRESENT ON BOTH SIDES OF A DIALYZER MEMBRANE
Bibliographic record
Abstract
The diffusion of waste products across dialyzer membranes is known to be proportional to the blood concentration entering the filter according to the formula J=KCbi. This formula is valid also when diffusion is combined with convection due to ultrafiltration (Quf). Theoretical expressions for the proportionality constant, the clearance K, have been developed under quite general conditions. For solutes that are present both in the blood and in the dialysis fluid, like Sodium Chloride, Ross et al (ASME, 1973) showed that under certain conditions the transport rate will depend linearly also on the concentration Cdi in the fresh dialysis fluid according to J=KbCbi-KdCdi. The constants Kb=K and Kd are in the general case complicated functions of the blood and dialysis fluid flow rates, Quf and the sieving properties. We have extended the results of Ross in two ways. Firstly, Ross only considered Quf that is equally distributed along the dialyzer. This is an unrealistic assumption, especially in HDF and HF treatments with large Quf leading to large pressure drops in the dialyzer. Our derivation allows for an arbitrary Quf distribution. Secondly, we were able to incorporate Villaroel's (Trans ASAIO, 1977) more realistic model for the local combination of diffusion and convection. For the case of negligible sieving effects, a good approximation for small solutes, we were also able to show that Kd=Kb-Quf irrespectively of the Quf distribution along the dialyzer. This is an important result since it is the 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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".