Accuracy of Peripheral Thermometers for Estimating Temperature
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Body temperature is commonly used to screen patients for infectious diseases, establish diagnoses, monitor therapy, and guide management decisions. PURPOSE: To determine the accuracy of peripheral thermometers for estimating core body temperature in adults and children. DATA SOURCES: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and CINAHL Plus from inception to July 2015. STUDY SELECTION: Prospective studies comparing the accuracy of peripheral (tympanic membrane, temporal artery, axillary, or oral) thermometers with central (pulmonary artery catheter, urinary bladder, esophageal, or rectal) thermometers. DATA EXTRACTION: 2 reviewers extracted data on study characteristics, methods, and outcomes and assessed the quality of individual studies. DATA SYNTHESIS: 75 studies (8682 patients) were included. Most studies were at high or unclear risk of patient selection bias (74%) or index test bias (67%). Compared with central thermometers, peripheral thermometers had pooled 95% limits of agreement (random-effects meta-analysis) outside the predefined clinically acceptable range (± 0.5 °C), especially among patients with fever (-1.44 °C to 1.46 °C for adults; -1.49 °C to 0.43 °C for children) and hypothermia (-2.07 °C to 1.90 °C for adults; no data for children). For detection of fever (bivariate random-effects meta-analysis), sensitivity was low (64% [95% CI, 55% to 72%]; I2 = 95.7%; P < 0.001) but specificity was high (96% [CI, 93% to 97%]; I2 = 96.3%; P < 0.001). Only 1 study reported sensitivity and specificity for the detection of hypothermia. LIMITATIONS: High-quality data for some temperature measurement techniques are limited. Pooled data are associated with interstudy heterogeneity that is not fully explained by stratified and metaregression analyses. CONCLUSION: Peripheral thermometers do not have clinically acceptable accuracy and should not be used when accurate measurement of body temperature will influence clinical decisions. PRIMARY FUNDING SOURCE: None.
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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 | 0.001 | 0.006 |
| 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 it