Review of Fall Armyworm (Lepidoptera: Noctuidae) Genetic Complexity and Migration
Bibliographic record
Abstract
The fall armyworm, Spodoptera frugiperda (J. E. Smith) is a significant economic pest in the western hemisphere, causing substantial losses in corn, sorghum, forage, and turf grasses. Although fall armyworm does not survive severe winters, it infests most of the central and eastern United States and Canada because of annual migrations from overwintering sites in Florida and Texas. A detailed description of these movements is a prerequisite for identifying the factors that determine the timing and direction of migration and for developing models that can predict the severity of infestations at the migratory destinations. Complicating this effort is genetic heterogeneity within the species, which increases phenotypic variability. Particularly important are 2 “host strains”, defined by a preferential association with either large grasses (designated corn-strain), such as corn and sorghum, or smaller grasses (designated rice-strain), such as rice and bermudagrass. This paper reviews recent studies examining the genetic complexity of fall armyworm populations, including characteristics of the 2 strains and the possibility of subgroups within strains. The use of this information to monitor short and long distance movements is discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".