Microscale ecotoxicity testing of Moselle river watershed (Lorraine Province, France) sediments
Bibliographic record
Abstract
The ecotoxic potential of seven Moselle river watershed sediments was assessed with a battery of bioassays comprised of rapid phototrophic [LuminoTox solid phase (L-SPA) and elutriate (L-ELU) assays] and bacterial [Microtox solid phase assay (M-SPA)] exposure tests, as well as with two micro-invertebrate solid phase tests conducted with Hydra attenuata (lethal and sublethal effects solid phase assay, HL-SPA and HSL-SPA) and Chironomus riparius. Measured effects of sediments and their elutriates were varied and reflected responses that were ecotoxicity test-, endpoint- and site-dependent, suggesting some degree of risk toward benthic and water column organisms, respectively, at specific sites. Correlation analysis demonstrated that L-SPA and M-SPA ecotoxicity responses were significantly linked with the Hydra HSL-SPA assay, indicating their ability to predict ecotoxicity towards an invertebrate taxonomic group representing secondary consumers. While the L-SPA and M-SPA assays hold promise as rapid screens for sediment ecotoxicity, correlation analysis with grain size (L-SPA: r=-0.795, P=0.033; M-SPA: r=-0.73, P=0.07) points out that their responses can be influenced by the presence of fines (i.e., sediment particles ≤0.063 mm in size) and that this information is essential to properly interpret ecotoxicity data generated with these assays. Finally, notable differences observed in trophic level sensitivities once again recall the importance of employing a test battery to adequately appraise the ecotoxicity of sediments.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".