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Record W2354879722 · doi:10.1371/journal.pone.0154965

Impact of Next Generation Sequencing on the Organization and Funding of Returning Research Results: Survey of Canadian Research Ethics Boards Members

2016· article· en· W2354879722 on OpenAlexafffundabout
Iris Jaitovich Groisman, Béatrice Godard

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversité de Montréal
FundersUniversité de Montréal
KeywordsResearch ethicsBusinessPublic relationsPsychologyPolitical scienceBiologyBiotechnology

Abstract

fetched live from OpenAlex

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.

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

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 armCategoriesStudy designConfidence
gemmaMetaresearchResearch integrity
Domain: Methods · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Observationalmedium
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.079
metaresearch head score (Gemma)0.499
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0790.499
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.939
GPT teacher head0.600
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

MetaresearchResearch integrity

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational
DomainMethods
GenreEmpirical

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".

Quick stats

Citations5
Published2016
Admission routes3
Has abstractyes

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