General mechanisms of coagulation and targets of anticoagulants (Section I)
Bibliographic record
Abstract
Contrary to previous models based on plasma, coagulation processes are currently believed to be mostly cell surface-based, including three overlapping phases: initiation, when tissue factor-expressing cells and microparticles are exposed to plasma; amplification, whereby small amounts of thrombin induce platelet activation and aggregation, and promote activation of factors (F)V, FVIII and FXI on platelet surfaces; and propagation, in which the Xase (tenase) and prothrombinase complexes are formed, producing a burst of thrombin and the cleavage of fibrinogen to fibrin. Thrombin exerts a number of additional biological actions, including platelet activation, amplification and self-inhibition of coagulation, clot stabilisation and anti-fibrinolysis, in processes occurring in the proximity of vessel injury, tightly regulated by a series of inhibitory mechanisms. "Classical" anticoagulants, including heparin and vitamin K antagonists, typically target multiple coagulation steps. A number of new anticoagulants, already developed or under development, target specific steps in the process, inhibiting a single coagulation factor or mimicking natural coagulation inhibitors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".