Call for a Singapore National Action Plan for Sepsis (SNAPS): Stop sepsis, save lives
Bibliographic record
Abstract
Sepsis is a life-threatening organ dysfunction syndrome caused by a dysregulated host response to an infection.1 It affects up to 48.9 million people globally every year and causes 11 million sepsis-related deaths, accounting for 1 in every 5 deaths worldwide.2 The huge disease burden leads to significant consumption of healthcare resources due to longer hospitalisation and the need for intensive care.3 The resultant economic impact is tremendous; for instance, the 1-year incremental costs of sepsis to the healthcare system in Ontario, Canada approximates CAD 1 billion.3 In addition to the complexity of care required for sepsis, the higher healthcare costs incurred may be explained by the post-sepsis syndrome. Sequelae of sepsis include physical, psychological and medical complications.4
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.060 | 0.023 |
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".