Western Washington weed control guide: ornamental bulbs (iris, narcissi, tulips)
Bibliographic record
Abstract
ORNAMENTAL BULBS (IRIS, NARCISSI, TULIPS)Weed infestations in bulb plantings reduce yields and size of bulbs, impair quality, and seriously interfere with harvest operations.There are three separate and distinct weed problems: perennials, winter annuals, and summer annuals. PerennialsAt present, there are no chemicals which will kill perennial weeds without causing bulb injury.Therefore, perennials must be eliminated before bulbs are planted.Tillage plus cropping is an effective program for reducing large infestations.The time needed to obtain control by clean cultivation depends on climate, soil type, weed species, etc.It can be shortened by growing competitive crops-such as alfalfa, rye, peas, etc., or annual row crops.In addition, herbicides can be used in combination with tillage to give better control of many weeds.The perennial weeds most common on land suited to bulbs are field horsetail, quackgrass, and Canada thistle.If possible, avoid planting bulbs in perennial weed-infested fields.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".