Influence of acidic to basic water pH and natural organic matter on aluminum accumulation by gills of rainbow trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
Juvenile rainbow trout (Oncorhynchus mykiss) (∼0.6 g) were exposed to 3 µmol Al·L1in ion-poor water adjusted to pH 410 in the absence or presence of natural organic matter (NOM). Aluminum accumulation by trout gills was highest at pH 68, there was moderate Al accumulation by trout gills at pH 5 and 9, and trout at pH 4 and 10 did not accumulate any Al on their gills. NOM at 5 mg C·L1eliminated Al accumulation by trout gills at all water pHs. These results are explained by NOM complexing Al and keeping Al in solution but off the gills, by H+competition with Al3+at low pH, by poor binding of the Al(OH)4anion to negatively charged gills at high pH, and by polymerization and precipitation of Al onto the gills at intermediate water pH, especially if water pH in the gill micro environment is considered. Increased fish mortality at pH 10 in the presence of NOM is explained by the indirect effect of NOM tying up the limited amount of Ca in the ion-poor water.
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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) | 0.001 | 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".