Bibliographic record
Abstract
The aim of this paper is to provide an analytical survey of the information available on the development of past and present surgical techniques, and to make projections for the future. For the purposes of this paper, the Past starts in the Neolithic period and ends in the 1800s. In this context, I have divided the Past into Prehistoric, Ancient and Middle Ages, and this period ends in the second half of the 19th century when the major obstacles to the further development of surgery, such as overcoming pain and infection, were removed. We will discuss the development of surgical techniques, and the obstacles and opportunities prevalent in these periods. In the context of this paper, the Present begins in 1867, when Louis Pasteur discovered microorganisms, and ends in the present day. There have been many important changes in the development of surgical techniques during this period, such as the transfer of surgery from the unsterile operating room to the modern hospital operating theater, the development of advanced and specialized surgical practices, such as transplants and laparoscopy, and minimally invasive surgical methods, robotic and Natural Orifice Transluminal Endoscopic Surgery. It is very difficult to foresee how surgical techniques will develop in the Future because of the unpredictable nature of technological progress. Therefore, in this paper, the forecast for the Future is limited to the next 50- 100 years and is a realistic calculation based on already existing technologies. In this context, the Future is divided into the development of surgical techniques that will develop in the near and distant future. It is anticipated that this overview will shed light on the historical perspective of surgical techniques and stimulate interest in their further development.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".