Bibliographic record
Abstract
Though it is commonly believed that two hours of fasting is required to minimize the risk of regurgitation and aspiration of gastric contents for clear liquids, there may be well defined benefits for shortening this time in the pediatric population. These include motre optimal hydration status, higher success rate of intravenous cannulation, decreased hypotension under anesthesia, and decreased parental and patient distress preoperatively. In fact, many society guidelines globally have shifted to a 1-hour fasting limit for clear liquids for pediatric patients. Notable organizations includes the Australian and New Zealand College of Anaesthetists, the Association of Paediatric Anaesthetists of Great Britain and Ireland, the European Society of Anaesthesiology and Intensive Care (ESAIC), L’Association Des Anesthésistes‐Réanimateurs Pédiatriques d’Expression Française, and the Canadian Anesthesiologists’ Society. Dalal and colleagues surveyed members of PALC (Pediatric Anesthesia Leadership Council). Results from their survey indicate that there is a growing trend towards reducing fasting times for clear liquids in children presenting for surgery. This infographic summarizes their findings. The reader is strongly encouraged to review the cited article for a more thorough appreciation of this topic.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".