Bibliographic record
Abstract
The current trend in all fields of surgery is towards less invasive procedures with shorter hospital stays. The reasons for this change include convenience to patients, optimal resource utilization, and cost saving. Technological advances in neurosurgery, aided by improvements in anesthesia, have resulted in surgery that is faster, simpler, and safer with excellent perioperative recovery. As a result of improved outcomes, some centers are performing brain tumor surgery on an outpatient basis, wherein patients arrive at the hospital the morning of their procedure and leave the hospital the same evening, thus avoiding an overnight stay in the hospital. In addition to the medical benefits of the outpatient procedure, its impact on patient satisfaction is substantial. The economic benefits are extremely favorable for the patient, physician, as well as the hospital. In high volume centers, a day surgery program can exist alongside those for elective and emergency surgeries, providing another pathway for patient care. However, due to skepticism surrounding the medicolegal aspects, and how radical the concept at first sounds, these procedures have not gained widespread popularity. We provide an overview of outpatient brain tumor surgery in the western world, discussing the socioeconomic, medicolegal, and ethical issues related to its adaptability in a developing nation.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".