Tissue-based risk assessment of great blue heron (<i>Ardea herodias</i>) exposed to PCDD/DF in the Tittabawassee River floodplain, Michigan, USA
Bibliographic record
Abstract
Concentrations of dioxin-like compounds, primarily polychlorinated dibenzofurans (PCDFs), in soils and sediments of the Tittabawassee River (TR) and associated floodplains downstream of Midland, Michigan, USA, were greater than upstream sites and prompted a site-specific risk assessment of great blue herons (GBH). Tissue exposure of PCDF and polychlorinated dibenzo-p-dioxins (PCDDs) was assessed in multiple GBH tissue types, including blood plasma of adults and eggs, as well as blood plasma, adipose, liver, and muscle of nestlings. Adult GBH exposure was associated with foraging area and age class, with concentrations of PCDD/DF being greater in blood plasma of adult GBH foraging in the TR compared with those foraging in upstream reference areas and in older birds as compared with their younger cohorts. Concentrations of PCDD/DFs and dioxin-like polychlorinated biphenyls (PCBs) in eggs and nestling tissues of GBH collected from rookeries within the TR floodplain were generally similar among rookeries. Mean concentrations of PCDD/DFs in eggs of GBH ranged from 45 to 67 ng/kg, wet weight for the rookeries studied, with a maximum concentration of 210 ng/kg, wet weight observed. Adipose consistently had the greatest concentration of PCDD/DFs of all tissues collected from nestlings of GBH, ranging from 98 to 430 ng/kg, wet weight. Potential for adverse population-level effects from site-specific contaminant exposures were evaluated by comparison with selected toxicity reference values (TRVs). Minimal risk of adverse population-level effects were predicted when exposures measured in tissues of GBH collected from rookeries within the TR were compared with appropriate TRVs. This prediction is consistent with site-specific measures of population condition, which included clutch size and number of nestlings per successful nest.
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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 | 0.000 | 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".