Comprehensive re-analysis of archived herring gull eggs reconstructs historical temporal trends in chlorinated hydrocarbon contamination in Lake Ontario and Green Bay, Lake Michigan, 1971–1982
Bibliographic record
Abstract
Herring gull egg homogenates collected between 1971 and 1982 from a colony in central Lake Ontario (Scotch Bonnet Island) and from a colony in central Green Bay, Lake Michigan (Big Sister Island) were archived in the Canadian Wildlife Service Specimen Bank. Pooled samples (N = 10) were exhaustively analyzed in 1993 for a wide range of individual chlorinated hydrocarbon contaminant (CHC) compounds: DDT, mirex and chlordane compounds and metabolites, chlorobenzenes (CBzs), dieldrin, chlorostyrenes (CSs), hexachlorocyclohexanes (HCHs), polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), and 87 PCB congeners, including the TCDD-like non-ortho and mono-ortho congeners. PCBs and DDTs were the dominant residues in eggs from both Lake Ontario (31-242 mg kg(-1) and 9-64 mg kg(-1)) and Green Bay (34-133 mg kg(-1) and 14-91 mg kg(-1)). SigmaPCBs declined by a factor of 4-5 and DDTs a factor of 4-7 at both colonies between 1971 and 1982. Lake Ontario eggs had significantly higher residues of 2,3,7,8-TCDD (0.2-2.0 microg kg(-1)), HCBz (0.1-4.7 mg kg(-1)), OCS (0.03-0.45 mg kg(-1)), three HpCSs (0.13-0.97 mg kg(-1)), mirex and mirex photodegradation products (2.1-9.2 mg kg(-1)) than Green Bay eggs. HCBz levels in Lake Ontario eggs declined a factor of 40, TCDD and chlorostyrenes a factor of 8-10, and mirex a factor of 4 between 1971-1978. Green Bay eggs had slightly higher levels of chlordane-related compounds, dieldrin and beta-HCH than Lake Ontario eggs. There were no consistent or strong trends in residue levels of these pesticides, PCDDs (except TCDD) and PCDFs in either lake, indicating that rates of input and removal of these CHCs in the lakes were much closer in the early 1970s than was the case for the other compounds.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".