Bibliographic record
Abstract
The peculiar pathogenesis of heparin-induced thrombocytopenia (HIT), involving a "self" antigen-platelet factor 4 (PF4) bound to heparin-and resulting antibody-mediated platelet activation, is a model for thrombosis triggered by drug-induced autoimmunity. The high probability of forming an immune response to heparin, and the highly-variable clinical significance of a positive laboratory test-depending on the type of assay and the magnitude of a given positive test result-provides lessons regarding appropriate interpretation of diagnostic laboratory testing in the context of pretest probability. The relatively high risk of inducing microvascular thrombosis due to coumarin-induced vitamin K antagonism attests to the dangers of a compromised protein C natural anticoagulant system in the setting of a hypercoagulability state such as HIT. Unusual immunologic features of HIT, such as the dissociation between immunogenicity (induction of immune response) and cross-reactivity (capacity to form the antigens recognized by HIT antibodies)of the implicated polysaccharide anticoagulants, and the generally rapid formation and disappearance of anti-PF4/heparin antibodies, suggest that further lessons regarding HIT immunopathogenesis remain to be learned.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".