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Record W2566791352 · doi:10.5539/ijb.v9n1p18

How to Balance the Risk and Benefit of Dual Use Research of Concern

2016· article· en· W2566791352 on OpenAlexvenueno aff
Ngoc B. Huynh

Bibliographic record

VenueInternational Journal of Biology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsnot available
Fundersnot available
KeywordsDual (grammatical number)Balance (ability)PublishingInfluenza A virus subtype H5N1Public healthDual roleBusinessMedical researchRisk analysis (engineering)Public relationsPolitical scienceMedicineLaw

Abstract

fetched live from OpenAlex

Dual use research on H5N1 Influenza is a big debate topic as technologies in research improve. Once DURC research is published, these studies could be misused by bioterrorist and considered a potential risk for public health with individual ill intent. There are many risks and benefits of performing and publishing of H5N1 studies in the United States. Some restriction in DURC are needed to take place to make sure the benefits outweigh the risks, so research could be performed to ensure the global health.

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)0.285
metaresearch head score (Gemma)0.629
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.980
Threshold uncertainty score0.882

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2850.629
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0060.003
Science and technology studies0.0030.014
Scholarly communication0.0170.021
Open science0.0040.011
Research integrity0.0200.011
Insufficient payload (model declined to judge)0.0110.004

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 head0.052
GPT teacher head0.357
Teacher spread0.305 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations0
Published2016
Admission routes1
Has abstractyes

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