The occurrence of cyst nematodes in agricultural fields of Southern Manitoba
Bibliographic record
Abstract
In southern Manitoba, Canada, a survey was carried out in 2012 and 2013 to determine the presence of Heteroderidae cyst-forming plant-parasitic nematodes, with a focus on the soybean cyst nematode (SCN) (Heterodera glycines). A total of 48 fields having grown soybean were sampled. A modified Fenwick elutriation-flotation technique was used to extract cysts with a 75% cyst recovery efficiency. Cyst population density averaged 0.9 cysts kg−1 soil, with a total of 65 cysts recovered. Preliminary screening of cysts, based on general body shape and vulval cone top structure, showed the presence of cysts belong to circumfenestrate, and ambifenestrate groups of cyst-forming nematodes. Limited morphological data was accessible due to poor quality or insufficient cysts for analysis; however, generated DNA sequences for nuclear rDNA ITS and D2-D3 expansion region of the 28S rRNA were obtained for four samples and matched sequences in GenBank for the cyst nematodes Cactodera milleri, C. torreyanae, C. weissi, C. estonica and unknown Cactodera species. Only one of the ambifenestrate cysts with a cone top structure of Heterodera species yielded DNA for analysis and its identification was ambiguous for soybean cyst nematode (SCN). None of the cysts were positive through SCN diagnostic PCR. Cactodera is not a pest of soybean or other crops in Manitoba. These cyst nematodes are likely to be naturally associated with weeds and grasses in the sampled fields or may be introduced from neighbouring states of the USA. Further annual surveys are needed and recommended in the near future to encompass more soybean fields and corroborate the absence of the pest.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".