Classificação de gravidade na pancreatite aguda
Bibliographic record
Abstract
Based on the Atlanta Classification, acute pancreatitis is classified according to its severity in either mild or severe acute pancreatitis. In recent years, several issues regarding acute pancreatitis have been discussed in the literature. These issues include how many categories of severity should be considered; whether or not a patient with organ failure holds similar holds severity of disease and prognosis of a patient with infected necrosis; the role of transient organ failure; and how to evaluate organ failure. The"Evidence-based Telemedicine - Trauma and Acute Care Surgery" (EBT-TACS) conducted a review of the recent literature on the topic, and critically appraised its most relevant pieces of evidence.. The articles discussed suggested classifying the severity of acute pancreatitis in three or four categories, rather than mild or severe only, and addressed which is the best score to assess organ failure. The following recommendations were proposed: (1) Acute pancreatitis should be classified into four categories: mild, moderate, severe and critical, which allows a better determination of the characteristics of patients, (2) Evaluation of organ failure with a severity score that preferably evaluate directly each organ failure, such as the SOFA and MODS (Marshall). The SOFA seems to have greater accuracy, but the MODS has better applicability due to its ease of use.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".