Snapping Turtles (<i>Chelydra serpentina</i>) as Bioindicators in Canadian Areas of Concern in the Great Lakes Basin. 1. Polybrominated Diphenyl Ethers, Polychlorinated Biphenyls, and Organochlorine Pesticides in Eggs
Bibliographic record
Abstract
We examined the concentrations and spatial patterns of congeners of PBDEs, PCBs, and organochlorine pesticides in snapping turtle (Chelydra serpentina) eggs from Areas of Concern (AOCs) on the Canadian shores of Lake Ontario, St. Lawrence River, and connecting channels. Eggs from Lyons Creek (Niagara River AOC) reflected a local PCB source over a range of 7.5 km (3.2-10.8) from the Welland Canal. PCB contamination in eggs declined with increasing distance from the Welland Canal, whereas the relative contribution of congeners associated with Aroclor 1248/1254 increased with sigma PCB concentrations. Compared to turtle eggs from other sites in Lake Erie and Lake Ontario, eggs from Lyons Creek and Snye Marsh had PCB congener patterns that reflected a strong contribution from Aroclor 1254. PCBs in the eggs were associated with industrial sources and reflected the composition of different Aroclor technical mixtures. Organochlorine pesticides in eggs tended to be highest at Hamilton Harbour and Bay of Quinte AOCs, and were dominated by DDE, sigma chlordane, and mirex. In contrast, PBDE congener patterns in turtle eggs resembled PentaBDE technical formulations regardless of absolute concentrations or location, and were largely associated with urban environments.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".