Delay Differential Equation Modelling of Erythropoiesis and Iron Metabolism of Blood Donors
Bibliographic record
Abstract
En second lieu, nous proposons un modèle mathématique combiné d'érythropoïèse et de métabolisation du fer.Il est important d'ajouter cette métabolisation dans la modélisation de l'érythropoïèse car la disponibilité en fer peut être un facteur limitant dans la synthèse de l'hémoglobine pendant l'érythropoïèse.Le modèle que nous proposons contient sept équations différentielles à retard couplées.Nous utilisons des retards distribués pour décrire l'effet de l'EPO sur les cellules précurseures d'érythrocytes et un retard constant pour l'effet de l'érythropoïèse sur la production d'hepcidine, principale hormone régulatrice de la métabolisation du fer.Nous effectuons des simulations numériques de ce modèle pour des dons de sang isolés ou répétés.A l'aide de ce modèle, nous testons vi Abrégé vii l'effet d'un allongement de l'intervalle inter-donation ainsi que d'une supplémentation en fer pour les donneurs de sang fréquents qui pourraient souffrir d'une déficience en fer pouvant affecter leur fréquence maximale de don.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".