Bibliographic record
Abstract
Pain is the perception of an unpleasant sensation to warn the body of tissue injury. Nociceptors send stimuli to the central nervous system via neurons that enter the spinal cord via the dorsal horn. The signal is then processed, integrated, and relayed to higher centres for interpretation. Surgery stimulates pain pathways due to the tissue injury that it creates and in this way a neuroendocrine cascade is set into action as a protective mechanism by the body. Cardiac patients and patients with cardiac risk factors pose a special risk when undergoing surgery. They exist in a state of altered vascular responsiveness due to endothelial injury and chronic inflammation of the vasculature. The physiologic response to pain may put cardiac patients at risk for cardiac events in the perioperative period. More recent methods in pain control, such as epidural anaesthesia, can be used to decrease the risk of cardiac events in these patients. Pain transmission and analgesia will be explored in this paper. Furthermore, the current American College of Cardiology and American Heart Association Task Force guidelines on the management of cardiac patients undergoing noncardiac surgery as well as the literature published since the release of these guidelinte will be discussed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".