Bibliographic record
Abstract
Abstract Native forbs are an essential component in the functioning and diversity of prairie communities. Aminocyclopyrachlor (AMCP) will effectively control many noxious weeds that invade prairie communities; however, its efficacy on desirable broadleaf plants is relatively unknown. Few field studies have been reported, and locating adequate populations of native forbs for evaluation of tolerance to herbicides is difficult. The susceptibility of 10 prairie forb species to AMCP was evaluated in the greenhouse. Species were chosen to correlate with a field study of AMCP and a previous greenhouse experiment. AMCP was applied at 0, 35, 70, and 105 g ha−1 with a methylated seed oil (MSO) plus silicone-based non-ionic surfactant (NIS) blend at 0.25% v/v when plants reached the growth stage simulating a spring treatment for weed control. Blueflag iris (Iris versicolor L.) and harebell (Campanula rotundifolia L.) were relatively tolerant and would likely be unharmed following an application of AMCP in the field. Wild licorice (Glycyrrhiza lepidota Pursh), prairie wild rose (Rosa arkansana Porter), purple prairie clover (Dalea purpurea Vent.), and wild bergamot (Monarda fistulosa L.) were moderately susceptible to AMCP; however, plants might regrow in the field, since some survived at the highest AMCP application rate (105 g ha−1) evaluated. Skyblue aster [Symphyotrichum oolentangiense (Riddell) G. L. Nesom], Canada goldenrod (Solidago canadensis L.), blue cardinal-flower (Lobelia siphilitica L.), and blacksamson echinacea (Echinacea angustifolia DC.) were susceptible to AMCP even when applied at 35 g ha−1. The susceptibility of greenhouse-grown forbs to AMCP was the same or similar to species evaluated in the field and can be used to predict native forb tolerance in the field.
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 | 0.000 | 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".