CERTIFIED WEED FREE FORAGE: AN EMERGING PROGRAM FOR WESTERN STATES
Bibliographic record
Abstract
Hay, raw feeds, and straw can contain germinable weed seeds if grown in fields where weeds are allowed to produce seeds, or rhizomes. These weeds can be spread into new areas by animal feed and mulches used for erosion control. Verifying that animal feed and mulch is weed free before it is used in an area can prevent the spread of weeds. Prevention programs are much simpler and cheaper than detection, control, or eradication programs for weeds that are already established. Certified weed free forage and mulch programs have been established in 13 western states and Canadian provinces since 1994. The purpose of these programs is to prevent the further spread of invasive noxious weeds. In California, the program has been initiated by three federal agencies, which have notified the public of their intention to close their lands to non-certified materials. The closure has a three-year timeline: the first season, 2002, drafting of certification procedures will be finished and education about the program, inspections and closures. The second year, closure are enacted with warnings to those who are not in compliance. The third year, full enforcement with citations will occur. There has been increasing concern by growers that the program will move beyond a voluntary, value-added marketing niche to a new minimum standard for market acceptability.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".