MétaCan
Menu
Back to cohort
Record W2021232783 · doi:10.4141/p05-114

Adventitious presence of GMOs: Scientific overview for Canadian grains

2006· article· en· W2021232783 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.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Plant Science · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
Fundersnot available
KeywordsCanolaTraceabilityBiotechnologyBiosafetyBusinessAgricultural scienceBiologyAgronomyMathematics

Abstract

fetched live from OpenAlex

The global expansion in the development and cultivation of genetically modified (GM) crops has increased international concern about adventitious presence of GM materials in non-GM seeds and grains. GM events in canola, corn, soybean, cotton, flax, papaya, potato, squash, sugar beet, and tomato have received regulatory approval in Canada. However, GM cultivars are only in commercial production for canola, corn and soybean. More than 30 GM events have been approved in these three crops. Cases of unapproved adventitious presence of GM materials that have impacted grain trading and handling in Canada and other countries include StarLink™ corn, GT200 canola, GM canola in mustard and recently Bt10 corn. Some countries have established tolerance and traceability requirements for adventitious presence of GMOs, while others are in the process of developing or adopting legislation. The threshold for labeling of adventitious presence of approved GM material in non-GM grain varies from 0.9% (e.g., EU) to 5% (e.g., Japan). Progress has been made in the development of DNA- and protein-based GMO detection methods. However, only a limited number of these detection methods have been internationally validated. The challenges for detection methods include sampling, a lack of certified reference material, a lack of DNA sequence information for the design of event-specific primers, and the sheer number of individual events that may be present and tested for. Current efforts by ISO and CEN will be valuable for establishing harmonized and standardized GMO detection methods. Key words: List of GM events, cases of AP, tolerance, traceability, detection methods, challenges

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)0.001
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 score0.865
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.037
GPT teacher head0.238
Teacher spread0.201 · 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