Seed burial by tillage promotes field recruitment of false cleavers (<i>Galium spurium</i>) and catchweed bedstraw (<i>Galium aparine</i>)
Bibliographic record
Abstract
False cleavers and catchweed bedstraw are problematic weeds of field crops in high-latitude regions of the northern Great Plains of North America. The abundance of these species has been increasing in areas of greater tillage intensity and frequency. Field experiments were established over 4 site-yr in Manitoba, Canada, and results indicated that the recruitment of false cleavers and catchweed bedstraw was strongly promoted by a single shallow tillage operation with a sweep cultivator in the spring. Percent recruitment levels in 2001 (pooled over sites) were 17 and 46% for the untilled and tilled treatments, respectively. In 2002, the percent recruitment levels for the untilled and tilled treatments, respectively, were 28 and 38% for the Komarno site and 13 and 28% for the Petersfield site. Only a few and minor differences in microsite conditions (soil temperature, soil moisture, and bulk density) resulted from the single spring tillage pass. The single tillage pass caused a significant relocation of simulated seeds (plastic beads) to below the soil surface and deeper into the soil profile (2–4 cm). Mean bulk density and volumetric soil moisture increased significantly with soil depth. The results of this study suggest that the positive effect of tillage on cleavers recruitment was not due to the effect of tillage on microsite conditions per se. Rather, the vertical redistribution of seed by tillage moved these seeds to a place in which the microsite conditions differed from those on the surface and were more favorable for recruitment. False cleavers and catchweed bedstraw recruitment is clearly promoted by tillage (even minor tillage) under field conditions, and farmers might be able to limit recruitment by limiting spring tillage.
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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 | 0.000 | 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) | 0.002 | 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".