025 Pea Leafminer, a New Pest of Leafy Vegetables in Ontario, Canada
Bibliographic record
Abstract
A new pest of leafy vegetables was responsible for considerable reductions in marketable yield of several late-season crops in the Holland/Bradford Marsh area (44°5'N, 79°35'W) of Ontario in 1999. The pea leafminer, Lyriomyza huidobrensis , was present in high populations (25/sweep) in fields of celery, Asian crucifer crops, and spinach during the months of August and September. The high populations were associated with extensive leaf mining of celery, root parsley, and edible dandelion. On other crops, including spinach and flat-flowering Chinese cabbage ( Brassica chinenesis group var. utilis) damage consisted of stippling of the leaves, as a result of feeding and possibly oviposition, but no leaf mining. The stippling was extensive and rendered these crops unmarketable. An other Asian crucifer, Chinese broccoli ( Brassica alboglabra ) exhibited high numbers of stipples on the leaves, but very low numbers of mines. The leaves of red beets exhibited a low incidence of mines, not enough to affect yield. This is the first report of the pea leafminer affecting field vegetables in this area and causing crop losses. Pictures of the pest and symptoms of damage to the crops will be presented.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".