MétaCan
Menu
Back to cohort
Record W2149672766 · doi:10.4269/ajtmh.2008.79.312

Ethical, Social, and Cultural Considerations for Site Selection for Research with Genetically Modified Mosquitoes

2008· article· en· W2149672766 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Tropical Medicine and Hygiene · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of TorontoCentre for Global Health ResearchSt. Michael's Hospital
Fundersnot available
KeywordsSelection (genetic algorithm)Process (computing)Site selectionGenetically modified organismKey (lock)BiotechnologyBiologyManagement scienceEngineering ethicsRisk analysis (engineering)Computer sciencePolitical scienceEngineeringBusinessEcologyArtificial intelligenceGenetics

Abstract

fetched live from OpenAlex

Recent advances in technology have made strategies for disease control using genetically modified (GM) vectors more plausible. Selecting an appropriate field site for research with GM mosquitoes may be one of the most complex and significant aspects of the research process. Among the key considerations of the process is the need to address ethical, legal, and cultural (ESC) issues. No guidelines have been developed to date for this complicated and sensitive process. In this paper, we describe a site selection process and a set of preliminary considerations for addressing the ESC aspects of a research program involving genetic strategies for the control of mosquitoes as vectors for dengue viruses. These considerations reflect some of the key ESC issues for site selection decisions for research with GM vectors.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.073
GPT teacher head0.407
Teacher spread0.334 · 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