PERCEPTION AND KNOWLEDGE OF BRAIN TUMOR BANKING AMONG CANADIAN NEUROSURGEONS
Bibliographic record
Abstract
Abstract Brain tumor banking provides an important resource for understanding the underlying pathophysiology of brain tumors. It requires a multidisciplinary team, including neurosurgeons who must recognize the importance of these banks and actively contribute. The perceptions and involvement of neurosurgeons regarding Canadian brain tumor banking remains to be studied. OBJECTIVE: This study aims to 1) assess current Canadian tumor tissue banking practices 2) determine the perception of neurosurgeons towards brain tumor tissue banks, and 3) uncover obstacles to tissue sample access. METHODS: A 26 question survey was conducted using Qualtrics and distributed to 178 Canadian neurosurgeons. Questions pertained to respondent demographics, tissue samples being banked, funding, and collaboration. RESULTS: 35 neurosurgeons completed the survey (19.66%). The majority of respondents treated adult populations (65.71%) and practiced in Ontario (57.14%). Most centers banked a variety of primary and metastatic brain tumors. 25.00% of respondents stated that their center collaborates with others. Personal communication was the most frequently stated method (58.33%) used to raise awareness of tumor banks. Funding was the most commonly mentioned obstacle to successful banking (70.37%). Banks are funded through research grants (30.76%), departmental support (30.76%), government funding (11.54%) and donations (26.92%). CONCLUSIONS: This study investigated neurosurgeons’ perceptions of brain tumor banking and the state of Canadian tumor banking. Despite numerous centers banking a variety of brain tumors, collaboration between institutes was limited. The greatest perceived obstacle is funding. Canadian brain banking may benefit from improved communication, collaboration, and funding.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".