Receptor characterization of nontarget butterflies for risk assessment of biological control with the egg parasitoid<i>Trichogramma minutum</i>(Hymenoptera: Trichogrammatidae)
Bibliographic record
Abstract
Abstract Receptor characterization (i.e., identifying what will be affected by an activity) is the first step in a risk assessment of biocontrol agents for insects. Development of a representative list of species at risk, based on ecological vulnerability, enables host-range screening of potential biocontrol agents on a manageable group of nontarget insects. A database of 153 species was used to characterize the butterflies potentially at risk from an inundative release of the egg parasitoidTrichogramma minutumRiley. Risk criteria for butterfly species included North American, Canadian, and Ontario geographic distributions; oviposition phenology; number of generations per year; overwintering stage; host-plant preferences; and egg mass type and location. Ecological vulnerability lists of butterfly species were generated for northern and southern Ontario; areas where there have been recent experimental inundative releases ofT. minutumfor the suppression of forest pests. Based on the above criteria, 2 species and a maximum of 27 species would be potentially at risk, and thus requiring host-range testing if an inundative release were considered for northern and southern Ontario, respectively. The number of species on the ecological vulnerability list for southern Ontario could be reduced to 12 species depending on the specific geographic location in southern Ontario of the inundative release. The six criteria used for receptor characterization forT. minutum, associated primarily with host-habitat location and host-location, can also be used for other parasitoids. They are components of any target host's biology, and thus will affect the scale and impact of any parasitoid attacking eggs, larvae, or pupae. Additional criteria for receptor characterization may also be added that will relate to the specifics of a parasitoid's biology and are associated with host acceptance and host suitability. Development of ecologically based vulnerability lists should become standard practice in determining which nontarget species require host-range testing, for both inundative and classical biocontrol agents targeting insects, and for the potential impact of invasive species.
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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 | 0.000 | 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 | 0.000 | 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 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".