Bioassay-directed chemical analysis of sediments
Bibliographic record
Abstract
In the scope of this thesis a procedure for the bioassay-directed chemical analysis of contaminated sediments was developed. It comprises the detection of acute toxic and mutagenic effects and the identification of the chemicals responsible for them. Porewater samples and eluates, respectively, as well as organic sediment extracts were investigated for acute and mutagenic effects using the two bacterial bioassays Microtox "t"r"a"d"e"m"a"r"k and Mutatox "t"r"a"d"e"m"a"r"k. All extracts and porewater samples were also examined by a non-target screening analysis by HPLC/MS or GC/MS. If a sample was toxic, it was fractionated. The toxicity was measured again in the fractions and the screening analysis was repeated. Moderately contaminated sediment samples from the Rivers Elbe, Saale and Rhine as well as highly contaminated samples from Hamilton Harbour (Canada), Hamburger Hafen and the River Bilina (Czech Republic) were investigated that way. The extracts from the moderately contaminated sites only showed minor effects, which were not put down to particular chemicals. In the samples form the highly contaminated sites compounds like PAH or bisphenol A were responsible for the extract toxicities. The effects were reproduced and verified by the measurement of single reference compounds and mixtures in the bioassays. (orig.)
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".