The Biological and Agronomic (Non) Sense of Ex‐Ante Coexistence Measures
Bibliographic record
Abstract
ABSTRACT The biological and agronomic sensibility of ex‐ante coexistence measures used in different parts of the world is reviewed. These measures need to be commensurate with the biology of the crop and the genetically modified (GM) adventitious presence (AP) labeling thresholds imposed by government or industry. Excessive and inflexible measures or establishment of artificially low thresholds are not consistent with the intent of recommendations, namely to provide growers and consumers with practical choices. In the case study of Portugal, few ex‐post liability claims have been made and GM thresholds have rarely exceeded 0.9%. Giving farmers more flexibility or decision‐making ability in the ‘who, what, where, and how’ of implementing coexistence measures has been successful. Knowledge and experience gained in coexistence worldwide should inform and strengthen future measures or policies. As such, regular monitoring, analysis, and reporting of the efficiency and effectiveness of coexistence measures worldwide would be a useful mechanism for iterative learning and adaptation. Excessive and scientifically unjustifiable measures need to be weeded out.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".