The Effect of Eurasian watermilfoil metal accumulation on the activity of milfoil weevil populations in Sudbury, Ontario
Bibliographic record
Abstract
This paper explores patterns of metal accumulation in Eurasian watermilfoil (Myriophyllum spicatum), and determines whether populations of milfoil weevils (Euhrychiopsis lecontei) in the Sudbury region are visibly affected by these patterns. To investigate this relationship, milfoil patches in six Sudbury lakes, and one control lake (Baptiste Lake, near Bancroft, ON) were sampled for sediment and plant chemistry, as well as for milfoil weevil damage as a measure of weevil activity. Comparisons of sediment, milfoil root, and milfoil stem metal concentrations among the seven lakes found sediment metal concentrations of Cd, Cu, Ni, and Pb, were all lowest in the control lake, Baptiste. The greatest differences were found in Cu and Ni concentrations, which were approximately fifteen to eighty times higher in Sudbury. Milfoil metal concentrations in the root and stem were not strongly correlated to sediment concentrations indicating that total metal concentrations are not reflective of the available metal in the Sudbury Lakes. Weevil damage was weakly correlated with Cd/Zn ratios, but uncorrelated with all stem metal concentrations. Principal Components Analysis confirmed that metal accumulation in Eurasian milfoil could not predict milfoil weevil damage. It is unclear whether milfoil weevils are simply unaffected by metal contamination in their host plant, or whether the effect is too small to detect with this study design.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".