Bibliographic record
Abstract
Perennial weeds like Rumex spp. and Cirsium arvense are still difficult to control in organic farming systems. The presented results were part of a cooperative project within the Federal Organic Farming Scheme (BÖL) dealing with the control of perennial weeds. Aim of the project was to evaluate present strategies for controlling perennial weeds in organically managed farms and to determine new recommendations. A nation-wide survey of over 150 organic farmers in Germany showed, that ca. 30 % of the arable land is infested with the Canadian thistle (Cirsium arvense). Most of the farmers (n=140) have problems with C. arvense as well as Rumex spp. and/or Agropyron repens. The impact of soil tillage and crop rotation on controlling C. arvense in organic farming was investigated on an agricultural field organically managed at the BBA for several years. It could be proved that by growing highly competitive crops like clover-grass mixture and winter rye shoot densities of C. arvense could be reduced, partly in combination with an increased use of a wing share cultivator. After one-year clover-grass mixture, being mulched three times, the highest decrease of C. arvense abundances was found: At 73 % of the measuring points a decrease of shoot densities of over 50 % was observed. Another strategy, ploughing twice, in autumn and spring, reduced density of C. arvense to a similar extent. In contrast to this a high intensity of stubble cultivation (up to three uses) combined with less competitive crops was not successful. Dock species are presently a particular problem in organically managed grassland. Due to their varying reproduction and survival strategies up to now it has not been possible to control them effectively and above all permanently. The nationalwide survey showed that 85 % of the grassland farmer (n=108) have problems with Rumex spp.. 20 measures – cutting the dock manually or mechanically with WUZI (an automotive machine built by an Austrian farmer) - are an effective instrument for controlling dock. The disadvantage however is the amount of work and the costs this involves. As a result, only 4 % of the organic farmers actually employ direct control of dock at regular intervals, as the survey demonstrated. Here, the tested automotive machine WUZI offers an innovative answer.
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".