Bibliographic record
Abstract
Pulmonary embolism (PE) and deep vein thrombosis (DVT) are associated with considerable morbidity and mortality, mostly, in case of PE for its lack of sensitivity of its early detection. For as much as twenty-five percent of PE patients the primary clinical appearance is unexpected death. While PE is one of the most avertable causes of hospital associated deaths, its diagnostics can be extremely difficult. Newly increased interest in an inherited thrombophilic states has been provoked by the discovery of several common inherited abnormalities, i.e. the prothrombin (PT) gene G20210A, Factor V Leiden (FVL) mutation (Arg506Gln), hyperhomocystenemia and homocysteiuria, Wein-Penzing defect, Sticky Platelet Syndrome (SPS), Quebec platelet disorder (QPD) and Sickle Cell Disease (SCD). PE incidence rates increase exponentially with age for both men and women, as they might harbor more than one thrombophilic state. Although the impact of genetic factors on PE is to some extent documented with lacking taxonomy, its genetic testing as its prevention strategy fall short.In this review thrombophilic states are divided into inherited or acquired, and only the inherited and newly documented are more closely followed. Factors are further grouped based on its thrombophilic taxonomy into; inherited defects of coagulation, inherited defects of fibrinolysis, inherited defects of enzymatic pathway in relation to development of VTE and PE and inherited defects of platelets in relation to PE. It was beyond the scope of this review to follow all inherited and newly recognized factors and its association to VTE and PE; however the overall taxonomy makes this review clinically valuable i.e. in relation to genetic testing as PE prevention.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".