Perceptions regarding browntail moth (Lepidoptera: Erebidae) management during an outbreak in Maine
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 Browntail moth, Euproctis chrysorrhoea (L.) (Lepidoptera: Erebidae), is a long-established invasive outbreaking public health and tree pest that once spanned large areas of the northeastern United States and Maritime Canada. Its current range is Maine and Cape Cod, Massachusetts. A recent outbreak began in Maine in 2015 and has spread to areas where it has not been seen in over 75 yr. Historically, pest management during the outbreaks occurred at all levels, including state and federal, but current management is largely the responsibility of homeowners and municipalities. To understand Maine residents’ experiences with browntail moth and thoughts on management methods, a survey questionnaire was conducted. More than 10,000 participants were invited through mail and volunteer sampling, with over 3,200 usable responses. The survey also included an experiment that tested whether a list of pros and cons would affect approval of different management methods. Respondents reported seeking out browntail moth information and pesticide guidance from multiple sources including state resources and social media. Analyses found that previous experience with management methods and missing work due to the rash caused by the larvae setae were important factors influencing management approval, whereas providing a list of pros and cons was found to be a conditional predictor. Overall, respondents preferred management methods with minimal nontarget effects and wanted more information about local browntail moth management plans. This is the first published survey conducted during a browntail moth outbreak in Maine and provides important insights that could help guide future browntail moth management, policies, and research.
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.
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 | 0.001 |
| 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) | 0.001 | 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 it