Copper inhibition of phytoplankton in Saginaw Bay, Lake Huron
Bibliographic record
Abstract
Field surveys and bioassays during 1999 and 2000 demonstrated trace metal effects on the phytoplankton of inner and outer regions of Saginaw Bay, Lake Huron. Addition of as little as 1 µg·L1 copper suppressed algal biomass, measured as particulate chlorophyll a, compared with control treatments, additions of ethylenediaminetetraacetic acid, or additions of carrier water alone. Suppression effects of copper, added alone or in combination with cadmium, lead, and thallium, were evident in inner and outer regions of Saginaw Bay during both spring and summer when phytoplankton communities were composed alternatively of diatoms and cyanobacteria. Experimental treatments were conducted in parallel with measurements of metal concentrations and metal complexation capacities of lake water collected by ultraclean trace metal techniques. Despite apparent overchelation of dissolved copper by organic ligands in Saginaw Bay, additions of a few tens of nanomoles of copper per litre strongly reduces algal biomass compared with control treatments. These results suggest that metal concentrations in some Great Lakes waters in equilibrium with natural chelators may be above the essential requirements and potentially at levels of incipient toxicity to the native phytoplankton communities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".