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Record W4300125779 · doi:10.3109/9781420020229-33

Electrophrenic Respiration

2008· article· en· W4300125779 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsnot available
Fundersnot available
KeywordsRespirationEnvironmental scienceBiologyBotany

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.195
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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