Additional file 1 of Proximal deep vein thrombosis and pulmonary embolism in COVID-19 patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Additional file 1 Search strategies. Table S1. PRISMA checklist. Table S2. Newcastle-Ottawa scale for included cohort studies. Table S3. Detailed characteristics of included studies.Table S4. Detailed characteristics of participants. Table S5. VTE stratified by the type of anticoagulation (none, prophylactic, therapeutic). Figure S1. Funnel plot of:1a studies in medical ward ± ICU inpatients;1b studies in ICU only. Figure S2. Forrest plot of the estimated incidence of proximal DVT:2a stratified by medical ward and ICU;2b stratified by location and screening. Figure S3. Forrest plot of the estimated incidence of PE:3a stratified by general ward and ICU;3b stratified by location and screening. Figure S4. Forrest plot of the meta-analytic risk of VTE, restricted to medical inpatients without ICU stay. Figure S5. Sensitivity analysis, restricting to high-quality studies:5a stratified by location; b stratified by location and screening.
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 | 0.004 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.746 | 0.026 |
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".