Evaluation Of Sublethal Toxicity Of Nitrite To A Suite Of Aquatic Organisms In Support Of The Derivation Of A Chronic Environmental Water Quality Benchmark
Bibliographic record
Abstract
Abstract Nitrite is a naturally-occurring inorganic compound that occurs in aquatic environments as an intermediary between nitrate and ammonia in the nitrogen cycle. It is a contaminant of potential concern resulting from anthropogenic activities in some cases. While the acute toxicity of nitrite has been characterized in previous studies, its sublethal toxicity is less understood. To determine the sublethal toxicity of nitrite on freshwater organisms, a suite of organisms was tested including: two salmonids (Oncorhynchus mykiss and O. kisutch), an alga (Pseudokirchneriella subcapitata), an aquatic macrophyte (Lemna minor), and three invertebrates (Ceriodaphnia dubia, Chironomus dilutus, and Neocloeon triangulifer). Test organisms were exposed to nitrite concentrations ranging between 0.02 and 1.28 mg/L nitrite (NO2-N). The toxicity tests were conducted according to procedures specified in standardized methods, allowing for the estimation of multiple endpoints for each test species. Species sensitivity distributions (SSDs) were generated using endpoints from the toxicity testing results, as well as data from previous studies, from which water chemistry approximated that used in the tests (i.e., < 5 mg/L chloride, an important toxicity-modifying factor for nitrite). The mayfly, N. triangulifer, was the most sensitive species, followed by the two salmonids (which represented the second and third most sensitive species), although they were not as sensitive to nitrite exposure as reported in previous studies. The fifth percentile hazard concentration (HC5) generated from the SSD could be used for derivation of regulatory benchmarks and threshold values for site-specific aquatic risk assessments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".