Animal decisions and conservation: the recolonization of a severely polluted river by the Eurasian otter
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Animals make decisions relying on environmental cues associated to high survival or breeding success along their evolutionary history. However, because of rapid anthropogenic changes in the environment, they may lack useful cues, making bad decisions with potential consequences for individuals and populations. Contaminants are difficult or impossible to detect for animals, so polluted habitats could be used in spite of their dangerous effects. The Eurasian otter Lutra lutra reoccupied the Guadiamar River (SW Spain) <1 year after a toxic spill that killed the fauna living in it. The levels of heavy metals and arsenic (As) in the river trophic web at that moment were probably harmful for otters. To investigate this, we determined the amount of several heavy metals including copper, cadmium, zinc (Zn) and lead (Pb) and metalloids such as As in otter faeces and estimated the exposure of otters to these elements as average ingestion. Concentrations of Zn, Pb and As were statistically higher in faeces collected along the Guadiamar River than in those collected along the Guadalete River (reference area). An ‘average otter’ in the Guadiamar River would consume 3–4 mg of Pb and more than 5 mg of As daily. Such doses must be hazardous for the species and challenge the usual assertion that otter presence is a good indicator of river quality.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it