Naked oat response to soil type and herbicides applied at two growing stages
Bibliographic record
Abstract
Naked oat (Avena sativa L.) harvested in the province of Quebec, Canada, develops on average 10% covered grains and sometimes more. The objective of this study was to determine the effect of soil type, herbicides and their application stages on the proportion of covered grains in naked oat genotypes. Three genotypes were evaluated over 2 yr at two experimental sites. At each site, trials were seeded on two different soil types and each entry was treated with one of three types of herbicides: bromoxynil/MCPA, dicamba/MCPA and thifensulfuron methyl/tribenuron methyl, and compared with a weed-free check. The herbicides were applied at Zadoks 12-13 and 22-23. Results showed that dicamba/MCPA herbicide, applied at Zadoks 12-13, increased covered grains compared with the weed-free check and more covered grains were produced with the application made at Zadoks 22-23. However, differences in genotype reactions were observed. Few differences were found among the other weed control treatments. The application of dicamba/MCPA at Zadoks 22-23 decreased yield and test weight, but increased kernel weight. The other weed control treatments had no effect on agronomic characteristics.Key words: Avena sativa, herbicide, dicamba/MCPA, soil type, covered grains
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".