Quantifying heat balance components in neonates nursed under radiant warmers in neonatal intensive care
Bibliographic record
Abstract
Neonatal intensive care units use radiant warmers (RW) to maintain stable body temperatures in many newborns. This study examined whether the rate of radiant heat required for heat balance (R req ) is equal to the rate of radiant heat provided by the RW (R prov ). A systematic evaluation of time‐dependent changes in heat balance components was conducted in 10 newborns (mass: 2829±636 g; age: 9.2±11.0 days; BSA: 0.19±0.03 m 2 ) nursed under RW. Metabolic rate, evaporative heat loss, convective and conductive heat flow, rectal temperature (T rec ) and mean skin temperature (T sk ) were measured continuously for 105 min. The rate of body heat storage (S) was calculated using a two‐compartment model of ‘core’ (T rec ) and ‘shell’ (T sk ) temperatures. Mean R prov (1.28±2.59 W) and R req (1.25±2.51W) were not significantly different (P=0.63). However, while the resultant mean change in body heat content after 105 min was low (+0.46±2.79 kJ) and not significantly different from zero (P>0.05), an acute time‐dependent change in body heat storage was evidenced by a mean positive heat storage component of +6.64±2.98 kJ and a mean negative heat storage component of −6.17±2.64 kJ. Accordingly, the mean difference between maximum and minimum values for T rec and T sk were 0.71±0.37°C and 2.18±0.81°C respectively. In conclusion, while RW maintain astable core temperature over a prolonged period, they induce acute bouts of heat imbalance. Supported by a NSERC Discovery Grant (O. Jay) & a CHEO Dept. of Surgery Research Grant (S. Chou).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".