How do we diagnose immune thrombocytopenia in 2018?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this report, we will review the various clinical and laboratory approaches to diagnosing immune thrombocytopenia (ITP), with a focus on its laboratory diagnosis. We will also summarize the results from a number of laboratories that have applied techniques to detect anti-platelet autoantibodies as diagnostic tests for ITP. Although there is considerable variability in methods among laboratories, there is general agreement that platelet autoantibody testing has a high specificity but low sensitivity. This suggests several possibilities: (1) the ideal test for ITP has yet to be developed, (2) current test methods need to be improved, or (3) ITP is the clinical expression of a variety of thrombocytopenic disorders with different underlying mechanisms. Even the clinical diagnosis of ITP is complex, and experienced clinicians do not always agree on whether a particular patient has ITP. Improvements in the diagnostic approach to ITP are necessary to improve the management of this disorder.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it