Factors affecting concentration of citrate in dialyzers when using citrate hemodialysate <i>in vitro</i>
Bibliographic record
Abstract
Objective: To observe the factors that affect the citrate concentration in hollow fiber when using citrate hemodialysate. Methods: By modeling hemodialysis in vitro, we studied 6 types of hemodialyzers at different blood flow rates, different dialysate flow‐rate, and different fluids in vitro to detect the citrate concentration in hollow fiber. Results: The citrate concentrations in different hemodialyzers were F60 > FB‐130UGA > GA‐HP130 > F6 > FB‐130AGA > WS‐70 in turn. The concentrations at different blood flow‐rates were different 100 mL/min > 200 mL/min. Conclusions: The concentration of citrate in hollow fiber is affected by different types of hemodialyzers and different blood as well as dialysate flow‐rates. To achieve anticoagulation when using citrate hemodialysate, we must select suitable hemodialyzer such as FB‐130UGA.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".