Bibliographic record
Abstract
We read with interest the study of Ross et al. (Ross et al. Anaesthesia 1999; 54: 1166-72) investigating the effect of the addition of isoflurane to Entonox (INO2). However, the twin aims of determining the practicality and safety of this mixture remains unanswered. With regard to the safety of this mixture, we note that no occupational exposure sampling of either isoflurane or nitrous oxide was carried out. Though the authors describe a scavenging mechanism, we are not informed of its effectiveness. Unless the labouring mother had been wearing a tight-fitting facemask, occupational exposure must have occurred. Under Control of Substances Hazardous to Health (COSHH) regulations [1], both of these agents have maximum exposure limits over an 8-h period. It is likely that these limits would be breached using INO2. A recent survey [2] showed that levels of nitrous oxide in delivery suites could exceed the maximum exposure limit four-fold. Another point that has not been considered is the environmental issue. Both nitrous oxide and isoflurane are greenhouse gases and are, in part, responsible for the depletion of the ozone layer. The Kyoto Conference in 1997 set standards for the reduction in nitrous oxide emission, anaesthetic use accounting for 10% of all nitrous oxide emissions [3]. The Montreal protocol likewise has set standards for the reduction in halogenated hydrocarbon production. Indeed, by 2030, it has been agreed that the production of all halogenated hydrocarbons should cease altogether. Over 165 countries worldwide have ratified this protocol. In light of the points raised above, we would be interested in the views of the authors regarding the future role of INO2 for pain relief in labouring women.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".