Guidance for Structuring a Pediatric Intermediate Care Unit
Bibliographic record
Abstract
The purpose of this policy statement is to update the 2004 American Academy of Pediatrics clinical report and provide enhanced guidance for institutions, administrators, and providers in the development and operation of a pediatric intermediate care unit (IMCU). Since 2004, there have been significant advances in pediatric medical, surgical, and critical care that have resulted in an evolution in the acuity and complexity of children potentially requiring IMCU admission. A group of 9 clinical experts in pediatric critical care, hospital medicine, intermediate care, and surgery developed a consensus on priority topics requiring updates, reviewed the relevant evidence, and, through a series of virtual meetings, developed the document. The intended audience of this policy statement is broad and includes pediatric critical care professionals, pediatric hospitalists, pediatric surgeons, other pediatric medical and surgical subspecialists, general pediatricians, nurses, social workers, care coordinators, hospital administrators, health care funders, and policymakers, primarily in resource-rich settings. Key priority topics were delineation of core principles for an IMCU, clarification of target populations, staffing recommendations, and payment.
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 | 0.043 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.020 | 0.014 |
| Insufficient payload (model declined to judge) | 0.021 | 0.011 |
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".