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Record W2774846165 · doi:10.12688/gatesopenres.12771.1

Informed consent in field trials of gene-drive mosquitoes

2017· preprint· en· W2774846165 on OpenAlexaff
Pamela A. Kolopack, James V. Lavery

Bibliographic record

VenueGates Open Research · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersBill and Melinda Gates Foundation
KeywordsInformed consentPopulationGene driveClinical trialField (mathematics)BioethicsPsychologyEngineering ethicsPolitical scienceMedicineLawEnvironmental healthAlternative medicineBiologyEngineeringPathologyGenetics

Abstract

fetched live from OpenAlex

The US National Academies' (NAS) recent report 'Gene Drives on the Horizon: Advancing Science, Navigating Uncertainty, and Aligning Research with Public Values' examines the requirements of responsible conduct in research involving gene drives in non-human organisms. Many of the complex ethical issues raised by the introduction of gene drive technologies for mosquito population control have been anticipated during the development and field-testing of earlier-generation genetic engineering approaches with mosquitoes. One issue-the requirement for informed consent in field trials-is not addressed explicitly in the NAS' report. Some commentators have presumed that informed consent should play a role as a protection for research participants in studies of genetically modified mosquitoes. Others have argued that there are no human subjects of field trials, so the informed consent requirement does not apply. It is both ethically and practically important that these presumptions are adequately scrutinized to ensure that any applications of informed consent in these trials are properly justified. We argue that informed consent from individual research participants in gene drive trials may be required: (1) when blood and other forms of clinical data are collected from them, as will likely be the case in some studies involving epidemiological endpoints, such as the incidence of new infections with dengue and malaria; (2) when they participate in social science and/or behavioral research involving the completion of surveys and questionnaires; or (3) when their home or property is accessed and the location recorded as a spatial variable for the release or collection of mosquitoes because the precise location of the household is important for entomological reasons and these data constitute identifiable private information at the household level. Importantly, most regulations and guidelines allow these requirements to be waived or modified, to various degrees, according to the judgment of Institutional Review Boards.

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 imitation

Not 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.

metaresearch head score (Codex)0.425
metaresearch head score (Gemma)0.375
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.425
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4250.375
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0030.003
Science and technology studies0.0070.015
Scholarly communication0.0090.012
Open science0.0070.007
Research integrity0.0560.025
Insufficient payload (model declined to judge)0.0190.009

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 head0.226
GPT teacher head0.543
Teacher spread0.317 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations55
Published2017
Admission routes1
Has abstractyes

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