A critique of studies evaluating glyphosate effects on diseases associated with <i>Fusarium</i> spp.
Bibliographic record
Abstract
Summary With the large‐scale adoption of glyphosate‐resistant crops in North America, there are concerns that non‐target microbial populations might be affected by increased frequency of glyphosate use. Stimulation of fungal species associated with crop diseases, including Fusarium spp., has been observed in laboratory and glasshouse experiments. Although field surveys in Saskatchewan detected positive associations between the incidence of Fusarium head blight and application of glyphosate formulations, few field experiments have been successful at demonstrating a stimulatory effect of glyphosate on crop diseases, including diseases associated with Fusarium spp. Taken at face value, there is little evidence from experimental field trials to support a causative link between glyphosate and crop diseases associated with Fusarium spp. However, we are concerned that the experimental field trials investigating links between glyphosate and Fusarium spp. are not representative of interactions that occur under actual farming conditions. In addition, inadequate consideration may have been given to microbial ecology during the design and maintenance of these experimental field trials. At this time, there is insufficient evidence to prove or disprove a link between glyphosate and crop diseases associated with Fusarium spp. and this area should receive high research priority, given the rapid and widespread increase in glyphosate use.
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 | 0.115 | 0.231 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".