Bibliographic record
Abstract
This chapter talks about diagnosis, management, treatment and prevention of quantitative platelet disorders as well as few case studies on this disorder. Thrombocytopenia, defined as a platelet count of less than 150 × 109/L, may be congenital or acquired. Immune thrombocytopenia (ITP) occurs secondary to autoantibodies that accelerate platelet destruction and additionally impair megakaryo-cytopoiesis. Neonatal thrombocytopenia, one of the most common hematological abnormalities observed in the neonatal period, may be classified based on the timing of the thrombocytopenia. Immediate bleeding is typical of thrombocytopenia, similar to other disorders of primary hemostasis, including platelet function defects and von Willebrand disease (VWD). Recurrent thrombocytopenia on discontinuation, arterial and venous thrombosis, bone marrow reticulin deposition, and hepatotoxicity are known side-effects. The therapeutic goal is to attain a safe platelet count that prevents major bleeding and allows a patient to lead a relatively normal life, rather than correcting the platelet counts to normal levels.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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".