Eat, Sleep, Console Approach
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: The opioid epidemic in the United States has resulted in an increased number of drug-exposed infants who are at risk for developing neonatal abstinence syndrome (NAS). Historically, these infants have been treated with the introduction and slow weaning of pharmaceuticals. Recently, a new model called Eat, Sleep, Console (ESC) has been developed that focuses on the comfort and care of these infants by maximizing nonpharmacologic methods, increasing family involvement in the treatment of their infant, and prn or "as needed" use of morphine. PURPOSE: The purpose of this evidenced-based practice brief was to summarize and critically review emerging research on the ESC method of managing NAS and develop a recommendation for implementing an ESC model. METHODS: A literature review was conducted using PubMed, Cochrane, and Google Scholar with a focus on ESC programs developed for treating infants with NAS. FINDING/RESULTS: Several studies were found with successful development and implementation of the ESC model. Studies supported the use of ESC to decrease length of stay, exposure to pharmacologic agents, and overall cost of treatment.Video Abstract Available at https://journals.lww.com/advancesinneonatalcare/Pages/videogallery.aspx?videoId=32&autoPlay=true.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.000 | 0.001 |
| 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