A response to ‘Temperature measurement after severe head injury’, Childs C <i>et al. Anaesthesia</i> 2004; 59: 192–3
Bibliographic record
Abstract
As a researcher who has been involved in temperature measurement studies for over a decade it was with concern that I read the article by Childs et al. in the February edition of your journal. The comment by these authors that ‘…the mouth…is not ideal for temperature measurement in intubated patients,…’ leads me to believe that they are not abreast with the literature in this area. There have been multiple studies over the last 20 years published in peer reviewed journals, including a state-of-the-science review published in 2000, to support the use of this site in patients who are orally intubated. Further, the evidence indicates that neither the temperature of the gases flowing witihin the oral tracheal tube nor the lack of a tight seal around the tube by patients significantly affect the measurements. I trust that your readers will be informed of this misinformation and that a correction will be issued in an upcoming issue of Anaesthesia.
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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 | 0.004 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.048 | 0.044 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".