Physiology, Pathophysiology, and Anesthetic Management of Patients with Respiratory Disease
Bibliographic record
Abstract
An understanding of respiratory function as it relates to anesthesia requires consideration of the neural control of respiration and its effect on alveolar ventilation (VA); the influence of anesthesia on the airway, chest wall, and lung volumes; and the alterations in ventilation-perfusion (V/Q) relationships during anesthesia. To describe the events of pulmonary ventilation, air in the lung has been subdivided into four different volumes and four different capacities: tidal volume, inspiratory reserve volume (IRV), expiratory reserve volume (ERV), and residual volume (RV). The volume of gas remaining in the lungs at the end of a normal expiration (that is, the functional residual capacity (FRC)) varies considerably as the position of the diaphragm, in particular, changes. Sedation and general anesthesia can produce profound changes in a patient's respiratory function, with the degree of change depending on the drugs employed, the species involved, the depth of anesthesia, the surgical procedure, and the health of the animal.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".