Development of a Recirculating Conveyance System to Facilitate Spot Application of Dichlobenil
Bibliographic record
Abstract
To facilitate spot application of dichlobenil (Casoron G-4) granular herbicide, a recirculating conveyance system is being developed and implemented on an existing Valmar 1255 broadcast applicator. As the product will need to be repeatedly cycled through the system, the project relies on Casoron G-4's ability to maintain its size and shape while being cycled. To evaluate Casoron G-4's granule robustness, the product was pneumatically cycled for one hour and the change in bulk density was evaluated. From this evaluation, it was determined that there was no significant difference in bulk density (p-value = 0.365) indicating that there was no significant granule breakdown. Being that the Valmar applicator already incorporates a pneumatic delivery system, it will only require modification to allow the product to cycle back into the hopper. Further testing is needed to determine the optimal hose sizing and pressures required by the system. Following this, a deflector plate will need to be designed to ensure that the proper granule spread is attained at ground level to ensure even product dispersion. Once the system has been developed and tested at lab scale the plan will be to incorporate it with a machine vision system to facilitate spot application of Casoron G-4 for fescue grass management in wild blueberries. That said the final system should be easily adaptable to a variety of alternative cropping systems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".