Increasing Use of Biocontrol in NYS Greenhouses with a Producer-based Biocontrol Mentoring Network
Bibliographic record
Abstract
There is a low adoption of biocontrol for pest management in NYS greenhouses although it has been used successfully elsewhere for years.? Because lack of experience is a deterrent for adoption, a project to encourage grower-to-grower training and discussion on biocontrol was initiated, funded by NYFVI.? Initial activities included a tour of Canadian greenhouses using biocontrol in 2007 and a series of 6 on-farm grower discussions held around the state in 2008.? Based on evaluations from the 2008 programs, 8 additional programs were held in 2009 to give growers hands-on experience with the most common biocontrol organisms used to control common greenhouse insects.? Preliminary results indicate that there was an increase in knowledge on the types of beneficials used in greenhouses, which are used to control specific pests, and how to determine if they are viable.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".