The History of Anesthesia and Anesthesiologists in Iran.
Bibliographic record
Abstract
The evolution of anesthesia and anesthesiology represents a pivotal chapter in the history of medical science, significantly enhancing patient care and surgical outcomes. General anesthesia, defined as the deliberate induction of a temporary state of pain relief, muscle paralysis, memory impairment, and unconsciousness, has revolutionized medical procedures by inhibiting the normal functioning of the central nervous system. In Iran, the journey of anesthesiology began with early contributions from ancient scholars and practitioners, whose innovative techniques laid the groundwork for future advancements. The field witnessed significant progress in the mid-20th century, aligning with global developments in medical science. Initially focused on intraoperative care, anesthesiology in Iran expanded to encompass preoperative evaluations, postoperative assessments, and comprehensive patient monitoring, addressing complications related to surgery and anesthesia. In addition to analyzing the evolution of anesthesiology from solely surgical intervention to a broader field encompassing preoperative evaluation, postoperative care, and critical care management, this paper addresses the challenges and opportunities facing anesthesia and anesthesiology in Iran, including the need for wider access to safe and reliable services and the integration of advanced technologies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".