Bibliographic record
Abstract
To the Editor: I am writing in response to an article recently published in Anesthesia & Analgesia(1). In this article temporal artery skin temperature, measured with the new and noninvasive infrared scanner SensorTouch, is compared to temperatures monitored at the pulmonary artery site in adults and bladder site in children. It is with considerable disappointment that I note a journal of the caliber of Anesthesia & Analgesia reporting on instrument testing when the accuracy (in vitro testing) of the reference instruments, in this case pulmonary artery and bladder catheters, is not reported. Although these instruments cannot be tested before insertion, they can be tested following removal from patients. Unfortunately the only reference made to the accuracy of these catheters to which the SensorTouch was compared is in a brief statement in the Methods section where the investigators report “The accuracy of these devices is ≈0.2°C.” Although the original research question posed in this study is important to clinical practice, I question if there is any point in reading the information past the above noted statement. Unless one knows the error of the reference instruments and makes the necessary corrections to the data for this inaccuracy, it is impossible to deduce the true accuracy of the test instrument. The science of temperature measurement has moved past the stage where sole reliance is placed upon the manufacturer’s reported accuracy. Researchers and journal reviewers need to routinely question results of studies where this information is not provided by the investigators if improved techniques are to be developed and new technology is to be fairly evaluated. Wendy M. Fallis, RN, PhD
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 | 0.005 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.013 | 0.014 |
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".