Surgical innovation or surgical evolution: an ethical and practical guide to handling novel neurosurgical procedures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECT: Surgical innovation is an important driver of improvements in technique and technology, which ultimately translates into improvements in patients' outcomes. Nevertheless, patients may face new risks of morbidity and mortality when surgical innovation is used, and well-intentioned surgical "experimentation" on patients must be regulated and monitored. In this paper the authors examine the challenges of defining surgical innovation and briefly review the literature on this challenging subject. METHODS: Using examples from the field of neurosurgery and in part from the personal experience of the senior author, the authors develop a model of levels of experimental acuity of surgical procedures and offer recommendations on how these procedures would best be regulated. CONCLUSIONS: The authors propose guidelines for determining the need for regulation of innovation. The potential role of institutional review boards in this process is highlighted.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it