MétaCan
Menu
Back to cohort
Record W2074968226 · doi:10.4161/21645698.2014.945880

Risk, regulation and biotechnology: The case of GM crops

2014· article· en· W2074968226 on OpenAlex
Stuart J. Smyth, Peter W.B. Phillips

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGM crops & food · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsNutrasourceSaskatoon Medical ImagingUniversity of Saskatchewan
FundersGenome PrairieGenome Canada
KeywordsBiotechnologyEuropean unionGenetically modified organismGenetically modified cropsBusinessLatin AmericansInternational tradeProduction (economics)PopulationAgricultural economicsPolitical scienceBiologyEconomicsLawEnvironmental health

Abstract

fetched live from OpenAlex

The global regulation of products of biotechnology is increasingly divided. Regulatory decisions for genetically modified (GM) crops in North America are predictable and efficient, with numerous countries in Latin and South America, Australia and Asia following this lead. While it might have been possible to argue that Europe's regulations were at one time based on real concerns about minimizing risks and ensuring health and safety, it is increasingly apparent that the entire European Union (EU) regulatory system for GM crops and foods is now driven by political agendas. Countries within the EU are at odds with each other as some have commercial production of GM crops, while others refuse to even develop regulations that could provide for the commercial release of GM crops. This divide in regulatory decision-making is affecting international grain trade, creating challenges for feeding an increasing global population.

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 score0.749
Threshold uncertainty score0.212

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 studies0.0000.000
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 head0.016
GPT teacher head0.221
Teacher spread0.205 · 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