Puzzling Elevation of Blood Lead Levels among Consumers of Freshwater Sportfish
Bibliographic record
Abstract
The authors evaluated lead exposure of Canadians (Montreal) who fished the nearby St. Lawrence River. From screening interviews conducted with 1,118 fishers on-site during the winter and fall of 1996, the authors selected 60 Montrealers who consumed at least one sportfish meal per week and 72 who consumed less than one sportfish meal per week. Fishers at the higher level of sportfish consumption had elevated blood lead concentrations, compared with fishers who ate little sportfish (geometric mean = 57.4 microg/l vs. 48.2 microg/l, respectively; p < .05). This result was surprising inasmuch as fish is not considered a significant source of lead. In addition to sportfish consumption, age, sex, occupation, smoking, and waterfowl consumption also showed independent associations with blood lead levels. Among frequent (i.e., > or = 1 meal/wk) consumers of sportfish, ingestion of waterfowl was associated with higher blood lead levels (geometric mean = 69.4 microg/l vs. 51.8 microg/l, respectively; p < .05); this association was not present for infrequent consumers. In multivariate analysis, the association of higher blood lead levels with sportfish consumption could be accounted for in large part by waterfowl consumption among frequent consumers of sportfish.
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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 | 0.002 |
| 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".