Acute toxicity largely reflects the salinity sensitivity of stream macroinvertebrates derived using field distributions
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
Two types of salinity tolerance information are commonly used for assessing salinity risk to freshwater organisms. These are data from laboratory experiments, usually acute (=96-h LC50) values, and field distributions. Both approaches have advantages and limitations, and their applicability to the formation of guidelines and assessment of risks is not clear. In the present study, the acute lethal tolerances (72-h LC50) and acute tolerance scores (ATS) of 37 macroinvertebrate families from Queensland, Australia, were compared with maximum field conductivities and previously derived salinity sensitivity scores (SSS). LC50 values were significantly correlated with maximal field conductivities and SSS. To investigate this relationship further, the changes in community structure related to an increase in salinity were assessed. A salinity index (SI) (based on cumulative SSS) and acute salinity index (ASI) (based on cumulative ATS) were calculated using an independent data set from south-east Queensland (429 samples) and compared with each other and actual conductivity levels. Both indices were significantly correlated with each other and followed a similar trend when plotted against actual conductivity. These results support the notion that salinity sensitivity of macroinvertebrates derived from acute toxicity experiments reflects sensitivities derived using field distributions. Definition of this relationship will allow the two sources of salinity sensitivity to be combined in a weight-of-evidence approach, resulting in a more robust data set with which to estimate safe salinity concentrations.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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 it