Suitability of felt traps to monitor oviposition by cabbage maggot (Diptera: Anthomyiidae)
Bibliographic record
Abstract
Abstract The effectiveness of felt egg traps to detect oviposition by the cabbage maggot,Delia radicum(L.), was studied under field conditions for cabbage,Brassica oleraceaL. var.capitataL. (Brassicaceae), and rutabaga,Brassica napusL. var.napobrassica(L.) Reichenb. (Brassicaceae), in 1994 and 1995. The numbers of eggs laid on traps were compared with the numbers deposited in the soil next to the plant. Also, the incidence of oviposition (i.e., the percentage of samples with eggs) on soil and traps was compared. A total of 5160 eggs was collected from 5208 samples, but just 16% of all samples had eggs. For cabbage, early in the 1994 season, the incidence of oviposition in soil samples was double that on traps, and the number of eggs per sample was greater also. Oviposition incidence and the number of eggs per sample during the rest of the summer were similar. In the 1995 cabbage trial, the incidence of oviposition early in the season was again higher in soil samples than on traps, and there were fewer eggs per trap than per soil sample. For rutabaga, the number of eggs was similar using both methods early in the second generation, but from mid-August there were more eggs per trap than per soil sample. The incidence of oviposition in the rutabaga trial was similar on traps and in soil through most of the experiment. In this study, felt traps did not adequately detect the timing of cabbage maggot oviposition in the critical early season.
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.
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) | 0.000 | 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".