Mathematical and Computational Modelling of the Lymphatic System: A Review
Bibliographic record
Abstract
The lymphatic system (LS) is a circulatory system composed of lymph vessels, which are similar to blood vessels.It gets rid of fluid (lymph) that has seeped into the tissues from the blood vessels and sends it back to the circulation through the lymph nodes.The LS's primary purposes are regulating fluid balance of the body and responding to bacteria, cancer cells, and cell products that may otherwise result in illness or diseases.The purpose of this paper is to present a summary of the directions in mathematical and computational modelling of the lymphatic system.A content analysis approach was used to identify relevant journal articles, and the major categories for organising the publications were Theoretical, Mathematical, Computational and Experimental.This paper synthesizes the findings and updates the field with the latest comprehensive reviews, including discussions on recent prototypes not covered in prior reviews.It offers a novel analysis framework that categorizes existing research into more refined sub-topics, facilitating easier navigation and understanding of the field's complexities, and it highlights emerging trends and gaps in the literature, directing future research towards underexplored areas within LS modelling.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".