Bibliographic record
Abstract
is an international peer-reviewed journal that publishes topical and innovative papers on weed science, in the English language. Its aim is to publish the best weed science from around the globe and to be the journal of choice for weed science researchers. It is the offi cial journal of the European Weed Research Society (http://www.ewrs.org). Papers are taken on all aspects of weeds, defi ned as plants that impact on economic, aesthetic or environmental aspects of any system. Topics include, amongst others, weed biology and control, herbicides, invasive plant species in all environments, population and spatial biology, modelling, genetics, biodiversity and parasitic plants. The journal welcomes submissions on work carried out in any part of the world and in all ecosystems. We encourage papers on both the positive and negative effects of plants, plant ecology and interactions with other taxa. We also invite contributions from forestry, horticulture, amenity and urban systems, and importantly from non-crop habitats including rangelands and conservation sites. Integrated crop and weed management is also a focus of the journal, built around primary plant production and its interactions with biotic, abiotic, social and economic environments to develop long-term sustainability. Thus, we are expanding the scope of the journal to cover cross-cutting issues in integrated crop management and the interactions with the range of disciplines across production and crop protection. In addition to research papers, the journal also seeks review articles, methods papers and shorter insights papers covering personal views, new methods and breaking news in weed science. The criteria Editors use for accepting manuscripts for publication are originality, relevance, scientifi c rigour and the clarity of presentation. There should be suffi cient material presented so that the information is of wider interest than just for local conditions. Thus, single experiments are unlikely to be acceptable. Research should cover suffi cient temporal and spatial variation to be able to make sound generalisations. For example, evaluation of herbicide effi cacy should be over more than one year at more than one site or soil type. Information for subscribers WEED RESEARCH is published in six issues per year. Institutional subscription prices for 2020 are: Print & Online: US$2553 (US), US$2976 (Rest of World), 1752 (Europe), 1383 (UK). Prices are exclusive of tax. Asia-Pacifi c GST, Canadian GST and European VAT will be applied at the appropriate rates. For more information on current tax rates,
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.780 | 0.697 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".