Factors and kinetics affecting platelet doublet formation in shear flow
Bibliographic record
Abstract
Platelet aggregation helps injured blood vessels heal.Activation of platelets without the need to repair injuries can lead to conditions such as thrombosis, embolism and strokes.Experiments with platelets and human aggregation factors are characterized by complexity, considerable variance, short raw material shelf life and high reagent cost.A model system based on the characteristics of fibrinogen-mediated aggregation was created using polyethyleneimine and ethanolamine covalently bound in a two-step process to carboxylate-modified microspheres.The functionalized spheres form aggregates in the presence of negatively-charged nanocrystalline cellulose and appear to simulate the behavior of fibrinogen-platelet systems well.The system aggregates fastest when approximately half of the available PEI chains are occupied.Increasing ion concentration leads to rapid decline of collision efficiency and ligand flocculation.Static incubation of spheres with excess ligand showed that excessive available ligand is not sufficient protection from unwanted aggregation.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".