Bibliographic record
Abstract
The primary goal of diagnostic testing for venous thromboembolism (VTE) is to identify all patients who could benefit from anticoagulant therapy. Test results that identify patients as having a ≤2% risk of VTE in the next 3 months are judged to exclude deep vein thrombosis (DVT) or pulmonary embolism (PE). Clinical evaluation, with assessment of: (1) clinical pretest probability (CPTP) for VTE; (2) likelihood of important alternative diagnoses; and (3) the probable yield of D-dimer and various imaging tests, guide which tests should be performed. The combination of nonhigh CPTP and negative D-dimer testing excludes DVT or PE in one-third to a half of outpatients. Venous ultrasound of the proximal veins, with or without examination of the distal veins, is the primary imaging test for leg and upper-extremity DVT. If a previous test is not available for comparison, the positive predictive value of ultrasound is low in patients with previous DVT. Computed tomography pulmonary angiography (CTPA) is the primary imaging test for PE and often yields an alternative diagnosis when there is no PE. Ventilation-perfusion scanning is associated with less radiation exposure than CTPA and is preferred in younger patients, particularly during pregnancy. If DVT or PE cannot be "ruled-in" or "ruled-out" by initial diagnostic testing, patients can usually be managed safely by: (1) withholding anticoagulant therapy; and (2) doing serial ultrasound examinations to detect new or extending DVT.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".