<i>Phoma macrostoma</i> : as a broad spectrum bioherbicide for turf grass and agricultural applications.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Phoma macrostoma Montagne 94-44B is an effective bioherbicide for broadleaved weed reduction. In 2016, Health Canada's Pest Management Regulatory Agency (PMRA), under the authority of the Pest Control Products Act and Regulations, granted full registration for the sale and use of the bioherbicide P. macrostoma Montagne 94-44B to control a broad spectrum of broadleaf weeds in established turfgrass and new seeding of grasses as well as in field grown nursery plants, trees and container-grown ornamentals. P. macrostoma 94-44B colonizes susceptible and non-susceptible plant roots, however, only in susceptible plants, such as Taraxacum officinale (dandelion), do mycelium proliferate around the vascular trachea interfering with the function of neighbouring cells while not entering them. Macrocidins, secondary metabolites secreted by P. macrostoma 94-44B mycelia, inhibit multiple steps in carotenoid precursor formation including phytoene desaturase and steps associated with β carotene and lutein carotenoid biogenesis, Fe and Mg chelation and OJIP chlorophyll fluorescence, thus uncoupling the light-harvesting complex of photosystem II from the reaction centre. The combined actions of P. macrostoma 94-44B and macrocidins elicit photobleaching of the leaves and eventual weed death. Research is underway to exploit Phoma's bioherbicidal actions for weed management in agriculture. P. macrostoma 94-44B can be used to reduce broadleaved weeds in crops such as wheat, corn, potato, forage grasses and established alfalfa (2nd growth or older). Soil residue studies reveal that neither P. macrostoma 94-44B nor macrocidins are present after 1 year suggesting that farmers could plant Phoma -sensitive crops such as legumes, flax or canola in subsequent years.
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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 | 0.000 | 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) | 0.000 | 0.002 |
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 it