Bibliographic record
Abstract
Glyphosate-resistant (GR) sugar beet became commercially available to US sugar beet growers in 2008 and was rapidly adopted. Prior to the availability of GR sugar beet, growers would commonly make 3-5 herbicide applications. This often resulted in some crop injury, but was accepted to reduce the impact of weeds. In addition, non-GR sugar beet was cultivated 1-3 times and often followed by hand weeding. The introduction of GR sugar beet drastically reduced the complexity of weed management. Concerns about GR weeds in the United States also apply to sugar beet growers. Changes in weed management strategies will be required to keep this technology. Sugar beet is arguably one of the most suitable crops for GR technology because: (1) none of the herbicides registered for use in this crop was very effective without risking crop injury; (2) sugar beet cannot be grown in the same field year after year owing to disease concerns and thus requires a 3-4 year rotation; (3) pollen-mediated gene flow is negligible from the sugar beet crop because it is a biennial and harvested before it flowers; (4) the processing of harvested roots to extract the sucrose rapidly degrades the DNA in the extracted raw juice and subsequent refining so that no DNA is present in the finished sugar; (5) studies have shown that processed GR beet sugar is identical to non-GR beet sugar, as well as cane sugar. © 2016 Society of Chemical Industry.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".