Bibliographic record
Abstract
Deep-vein thrombosis (DVT) and pulmonary embolism are among the most common complications of heparin-induced thrombocytopenia (HIT), an antibody-mediated adverse effect of heparin that leads paradoxically to in vivo activation of platelets and the coagulation system. Inappropriate treatment of HIT-associated DVT with warfarin can cause the DVT to progress to limb gangrene: this results from impaired ability of the protein C natural anticoagulant pathway to down-regulate thrombin generation, thus leading to microvascular thrombosis and tissue necrosis. Appreciation of the importance of coagulation system activation in HIT provides a rationale for treatments that reduce thrombin generation, either via inhibiting factor Xa (danaparoid) or via inhibiting thrombin directly (lepirudin). Clinicians should know how to distinguish HIT from other thrombocytopenic disorders: for example, thrombocytopenia associated with pulmonary embolism can mimic HIT (pseudo-HIT), and acute dyspnea that can mimic acute pulmonary embolism can result from acute in vivo platelet activation in a patient with HIT antibodies who receives heparin bolus therapy (pseudo-pulmonary embolism).
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) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".