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Record W2050411843 · doi:10.1071/ea04205

Honey produced from genetically modified canola (Brassica napus) nectar will not need to be labelled as a GM food under current Australian guidelines

2006· article· en· W2050411843 on OpenAlexaboutno aff
M. Hornitzky, Aida Ghalayini

Bibliographic record

VenueAustralian Journal of Experimental Agriculture · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsnot available
FundersRural Industries Research and Development Corporation
KeywordsCanolaBrassicaBiologyGenetically modified organismPollenAgronomyNectarBiotechnologyToxicologyBotany

Abstract

fetched live from OpenAlex

Food or ingredients labelled as genetically modified (GM) contain either new genetic material or protein as a result of genetic modification. In Australia, a 1% threshold, below which labelling is not required, exists for the unintended presence of GM material in non-GM foods. The canola pollen content by dry weight in a range of canola honey samples from diverse geographical areas in Australia was determined to be 0.2 ± 0.12%, well below the 1% threshold. Two GM canola honey samples sourced from Canada contained 0.19 and 0.24% of canola pollen. This work indicates honey derived from GM canola crops will not need to be labelled as a GM food.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.078
GPT teacher head0.321
Teacher spread0.242 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2006
Admission routes1
Has abstractyes

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