Bibliographic record
Abstract
The adoption of genetically engineered maize for herbicide tolerance has significantly impacted agricultural practices, particularly in weed management. This study examines the development, implementation, and consequences of herbicide-tolerant maize varieties. The introduction of transgenic maize expressing genes such as dicamba monooxygenase (DMO) and CP4-EPSPS has enabled higher tolerance levels to herbicides like dicamba and glyphosate, respectively, leading to improved weed control and reduced crop injury. However, the widespread use of these genetically modified (GM) crops has also led to the emergence of herbicide-resistant weeds, necessitating the development of dual herbicide-tolerant varieties and new herbicide tolerance traits. Meta-analyses and field studies indicate that while GM crops have reduced overall pesticide use and increased crop yields and farmer profits, the long-term sustainability of these benefits is challenged by evolving weed resistance. This study synthesizes findings from multiple studies to provide a comprehensive understanding of the agronomic, economic, and environmental impacts of herbicide-tolerant maize, highlighting both the advantages and the ongoing challenges in this field.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".