Bibliographic record
Abstract
Electrophrenic respiration was developed in 1948 by Sarnoff et al. (1) who reported successful ventilation among dogs, cats, rabbits, and monkeys when electrodes were attached directly to their phrenic nerves. In these studies they were able to achieve minute ventilation and blood gases comparable to those measured during periods of unassisted ventilation, noting the relationship between the applied voltage and the resultant respiratory volumes. In these animals electrophrenic respiration could maintain satisfactory blood gases for up to 22 hours (1). Since diaphragmatic stimulator implant surgery was developed for chronic ventilatory support in 1968, several thousand patients worldwide have benefited from its use (2). In 1973 Glenn and colleagues first reported on the effectiveness of diaphragmatic pacing among patients with quadriplegia and those with chronic alveolar hypoventilation (3). Commercially available systems are currently accessible from three sources worldwide-Avery Biomedical DevicesTM in the United States, AtrotechTM in Finland, and MedImplantTM in Austria. The only system approved for use by the FDA is the Avery Biomedical Devices system. At present this company is following 300 patients, 200 of whom are residents of the United States and 17 of whom are based in Canada. This number is small when considering that in the United States 4% of the annual 10,000 new spinal injury patients require mechanical ventilation (4) and that quadriplegia is not the only indication for phrenic pacing.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".