Exposure to neodymium blunts the hypoxic ventilatory response in fathead minnows ( <i>Pimephales promelas</i> )
Bibliographic record
Abstract
Abstract In hypoxia, the initial response in vertebrates is hyperventilation, known as the Hypoxic Ventilatory Response (HVR), which is a physiological reflex that allows fish to maintain adequate oxygen uptake. The severity of hypoxia in aquatic ecosystems is growing due to anthropogenic impacts. This is a concern with the recent evidence that metals can affect the ability of fishes to mount the HVR, potentially impacting survival. As Rare Earth Elements (REEs) increase in demand with the shift to a low-carbon economy, there is a critical need to understand their environmental consequences. Neodymium (Nd) is used in green technology and is one of the most critical REEs. Here, we investigate whether exposure to Nd will blunt the HVR in a toxicological model, the fathead minnow ( Pimephales promelas ). The fathead minnow will be exposed to hypoxia and Nd, and the ventilation rate will be observed and compared to controls to determine if there is a blunt in the HVR when the fish are exposed to both hypoxia and Nd. Nd caused a 31% decrease in the HVR and Nd accumulation in the gills was below the detection limit (LOD: 0.0681 µg/L). Toxicity testing with REEs during this time of economic growth is imperative for the protection of aquatic life in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".