Evaluation of the association between extravascular lung water and prognosis of sepsis
Bibliographic record
Abstract
BACKGROUND: The purpose of this study is to explore the association between extravascular lung water (EVLW) and prognosis of sepsis (PS). METHODS: We will carry out comprehensive literature search in electronic databases (PUBMED/MEDLINE, EMBASE, CENTRAL, WorldSciNet, PsycINFO, Allied and Complementary Medicine Database, CBM, and CNKI) and additional sources. All electronic databases will be searched from their initial to the present without language restrictions. Case-controlled studies reporting the association between EVLW and PS will be evaluated for inclusion. Outcomes of interest will include mortality rate, extravascular lung water index, pulmonary vascular permeability index, blood lactate clearance, oxygenation index, blood gas analysis, PaO2/FiO2, cardiac output index, global end diastolic volume index, intrathoracic blood volume index, systemic resistance index, acute physiology and chronic health scoring system II, and infection-related organ failure scoring system. Study quality will be evaluated using Newcastle-Ottawa Tool, and statistical analysis will be performed utilizing RevMan 5.4 software. RESULTS: This study will summarize the most recent evidence to investigate the association between EVLW and PS. CONCLUSIONS: The results of this study will provide an exhaustive view of the association between EVLW and PS. STUDY REGISTRATION OSF: osf.io/vhnxw.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".