Burrowing mayflies as indicators of ecosystem health: Status of populations in western Lake Erie, Saginaw Bay and Green Bay
Bibliographic record
Abstract
The U.S. Environmental Protection Agency and Environment Canada are supporting the development of indicators of ecosystem health that can be used to report on progress in restoring and maintaining the Great Lakes ecosystem, as called for in the Great Lakes Water Quality Agreement between the United States and Canada. One indicator under development is based on burrowing mayflies (Hexagenia: Ephemeroptera: Ephemeridae). We sampled in western Lake Erie, Saginaw Bay (Lake Huron), and Green Bay (Lake Michigan) in spring 2001 at 117 stations covering about 1,870 km2 of lake bed, to determine the status of nymphal populations of Hexagenia, and to provide information that would further the technical development of an indicator of ecosystem health based on Hexagenia. In western Lake Erie, density and biomass of nymphs were generally highest on fine-grained substrate in offshore waters and were lower on coarser substrates in near shore waters. Nymphs were virtually absent from Saginaw Bay, where only one nymph was collected at 28 stations. Nymphs were collected at only 6 of 48 stations in Green Bay, and density and biomass were highest at the northern end of the bay. Polluted sediments are likely responsible for the absence or low density and biomass of nymphs observed on fine-grained substrates in western Lake Erie, Saginaw Bay, and Green Bay, all of which historically supported abundant populations.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".