Insufficiency in a New Temporal-Artery Thermometer for Adult and Pediatric Patients
Bibliographic record
Abstract
UNLABELLED: SensorTouch is a new noninvasive temperature monitor and consists of an infrared scanner that detects the highest temperature on the skin of the forehead, presumably over the temporal artery. The device estimates core temperature (T(core)). We tested the hypothesis that the SensorTouch is sufficiently precise and accurate for routine clinical use. We studied adults (n = 15) and children (n = 16) who developed mild fever, a core temperature of at least 37.8 degrees C, after cardiopulmonary bypass. Temperature was recorded at 15-min intervals throughout recovery with the SensorTouch thermometer and from the pulmonary artery (adults) or bladder (children). Pulmonary artery (T(core)) and SensorTouch (T(st)) temperatures correlated poorly in adults: T(core) = 0.7. T(st) + 13, r(2) = 0.3. Infrared and pulmonary artery temperatures differed by 1.3 +/- 0.6 degrees C; 89% of the adult temperatures thus differed by more than 0.5 degrees C. Bladder and infrared temperatures correlated somewhat better in pediatric patients: T(core) = 0.9. T(st) + 12, r(2) = 0.6. Infrared and bladder temperatures in children differed by only 0.3 degrees C, but the SD of the difference was 0.5 degrees C. Thus, 31% of the values in the infants and children differed by more than 0.5 degrees C. IMPLICATIONS: We evaluated a noninvasive infrared forehead thermometer (SensorTouch) in adult and pediatric cardiac patients. Accuracy was poor in the adults and suboptimal in infants and children.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".