Are neurosurgeons prepared to electively resample glioblastoma in patients without symptomatic relapse? A qualitative study
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
Background This is a qualitative study designed to examine neurosurgeons' and neuro-oncologists' perceptions of resampling surgery for glioblastoma multiforme electively, post-therapy or at asymptomatic relapse. Methods Twenty-six neurosurgeons, three radiation oncologists and one neuro-oncologist were selected using convenience sampling and interviewed. Participants were presented with hypothetical scenarios in which resampling surgery was offered within a clinical trial and another in which the surgery was offered on a routine basis. Results Over half of the participants were interested in doing this within a clinical trial. About a quarter of the participants would be willing to consider routine resampling surgery if: (1) a resection were done rather than a simple biopsy; (2) they could wait until the patient becomes symptomatic and (3) there was a preliminary in vitro study with existing tumour samples to be able to offer patients some trial drugs. The remaining quarter of participants was entirely against the trial. Participants also expressed concerns about resource allocation, financial barriers, possibilities of patient coercion and the fear of patients' inability to offer true informed consent. Conclusion Overall, if surgeons are convinced of the benefits of the trial from their information from scientists, and they feel that patients are providing truly informed consent, then the majority would be willing to consider performing the surgery. Many surgeons would still feel uncomfortable with the procedure unless they are able to offer the patient some benefit from the procedure such that the risk to benefit ratio is balanced.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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