Skeletal Pathology in White Storks ( <i>Ciconia ciconia</i> ) Associated With Heavy Metal Contamination in Southwestern Spain
Bibliographic record
Abstract
In 1998, a mine tailings dyke in southwestern Spain broke, flooding the Agrio-Guadiamar river system with acid tailings up to the borders of one of the largest breeding colonies of white storks in the western Palearctic, Dehesa de Abajo. Over the following years, a high proportion of nestlings developed leg defects, prompting this study. Ten fledglings with leg deformities from the spill area were compared with 11 normal storks of the same year class from another region far from the spill. However, metals were analyzed as a continuum rather than by site, as reference birds also contained high levels of metals. Gross pathology of the legs was supported by histopathology, which showed that bone remodeling activity was greater in the deformed storks, which also had more irregular subperiosteal bone, and tended to have higher residual islets of cartilage in their metaphyses, which, in turn were related to metal contaminant residues. Both Ca and P in bone were affected independently by metals. Deformed birds had lower serum bone alkaline phosphatase. Bone malformations, measured by leg asymmetry, was only partially explained by bone metals, indicating that a combination of factors was involved with the abnormal development in these young storks.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".