Pandemic planning: Developing a triage framework for Neonatal Intensive Care Unit
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
Although the Covid-19 pandemic has not had a direct impact on neonates so far, it has raised concerns about resource distribution and showed that planning is required before the next crisis or pandemic. Resource allocation must consider unique Neonatal Intensive Care Unit (NICU) attributes, including physical space and equipment that may not be transferable to older populations, unique skills of NICU staff, inherent uncertainty in prognosis both antenatally and postnatally, possible biases against neonates, and the future pandemic disease's possible impact on neonates. We identified the need for a validated Neonatal Severity of Illness Prognostic Score to guide triage decisions. Based on this score, triage decisions are the responsibility of an informed triage team not involved in direct patient care. Support for the distress experienced by parents and staff is needed. This paper presents essential considerations in developing a practical framework for resources and triage in the NICU before, during and after a pandemic.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it