Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Sepsis is the leading cause of death in burns. Despite its importance, sepsis lacks a proper definition. An established definition will lead to early and accurate diagnosis, prompt treatment, and a reduced mortality rate. The aim of this work is to discuss current definitions and to look ahead at novel definitions with clinical implications. Method: A review of the current understanding of sepsis definitions in burns. Results: Adaptation of sepsis definitions in the general population and specific burn definitions have gotten better but still need improvements and, potentially, incorporation of molecular, laboratory, patient-specific, and clinical factors. This work includes the history, evolution, and predictive value of current definitions of sepsis in burns. A review of current and future markers of sepsis and potentially useful definitions are presented. Conclusions: Sepsis definitions have evolved over the last decades and will continue to do so. We believe the best definition in burn patients is the Sepsis-3 that was developed originally for critically ill patients. However, there are several studies investigating more specific definitions with better sensitivity and specificity.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it