Impact of Next Generation Sequencing on the Organization and Funding of Returning Research Results: Survey of Canadian Research Ethics Boards Members
Bibliographic record
Abstract
Research Ethics Boards (REBs) are expected to evaluate protocols planning the use of Next Generation Sequencing technologies (NGS), assuring that any genomic finding will be properly managed. As Canadian REBs play a central role in the disclosure of such results, we deemed it important to examine the views and experience of REB members on the return of aggregated research results, individual research results (IRRs) and incidental findings (IFs) in current genomic research. With this intent, we carried out a web-based survey, which showed that 59.7% of respondents viewed the change from traditional sequencing to NGS as more than a technical substitution, and that 77% of respondents agreed on the importance of returning aggregated research results, the most compelling reasons being the recognition of participants' contribution and increasing the awareness of scientific progress. As for IRRs specifically, 50% of respondents were in favour of conveying such information, even when they only indicated the probability that a condition may develop. Current regulations and risk to participants were considered equally important, and much more than financial costs, when considering the return of IRRs and IFs. Respondents indicated that the financial aspect of offering genetic counseling was the least important matter when assessing it as a requisite. Granting agencies were named as mainly responsible for funding, while the organizing and returning of IRRs and IFs belonged to researchers. However, views in these matters differ according to respondents' experience. Our results draw attention to the need for improved guidance when considering the organizational and financial aspects of returning genetic research results, so as to better fulfill the ethical and moral principles that are to guide such undertakings.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | medium |
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 | 0.051 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".