Toward management guidelines for soybean aphid, <i>Aphis glycines</i>, in Quebec. II. Spatial distribution of aphid populations in commercial soybean fields
Bibliographic record
Abstract
Abstract The study was conducted to document the spatial distribution of the soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), in commercial fields of soybean, Glycine max (L.) Merr. The abundance of aphids was assessed weekly at 12 sites in 2005 and 2006 on more than 135 georeferenced plants per site. Variograms and principal coordinates of neighbour matrices (PCNM) were used to detect significant spatial structures. Variograms indicated a spatially random distribution of aphid populations in a majority (84%) of fields-weeks. For the variograms with a defined structure, the variance between pairs of observations generally increased rapidly with the distance between plants up to a distance where it stabilized, a pattern adequately fitted by spherical models. Structured spatial distributions were more prevalent in 2005 than in 2006, especially at the end of the season. In 2006, PCNM analysis was more sensitive in detecting spatial trends than were variograms. PCNM analysis revealed significant patterns across a broad range of scales, with dominant periods averaging 22.6 and 47.1 m for the short and long transects, respectively. Sampling plants along a 100 m long transect at about 7.5 m intervals in soybean fields would allow detection of the spatial structures identified in this study.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 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".