Bibliographic record
Abstract
Venous thromboembolism (VTE) is a major problem in non-surgical patients admitted to the hospital, both during the hospitalization period and after discharge. Risk factors for VTE are well known and scoring systems have been published. Nevertheless, prophylaxis against VTE is in many hospitals used less often than ideal and also inappropriately. Electronic tools to alert the physicians to provide prophylaxis and suggest suitable measures have shown promising results with a reduction of clinically relevant VTE. Large randomized clinical trials have demonstrated efficacy of low molecular-weight heparin (LMWH), pentasaccharide(fondaparinux) and unfractionated heparin. The results were, however, driven by asymptomatic deep vein thrombosis (DVT), including distal DVT in some studies. A reduction of pulmonary embolism is achieved, but without any significant effect on the mortality. The agents are generally safe, with only a small increase of major bleeding, less with LMWH than with unfractionated heparin. The challenge is still to direct the efforts to the most appropriate patients.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".