Assessing the Usefulness of the Automated Monitoring Systems ECOTOX and DaphniaTox in an Integrated Early-Warning System for Drinking Water
Bibliographic record
Abstract
This study assesses the suitability of the behavioural image analysis systems ECOTOX and Daphnia Tox for inclusion in an integrated early-warning system for drinking water quality to be implemented in Canada. Results of behavioural parameters measured by ECOTOX using Euglena gracilis are compared to visual observations of E. gracilis behaviour after exposure to atrazine, tributyltin, and copper to determine the automated system's sensitivity. The usability of the Daphnia Tox automated system is assessed using the aquatic macroinvertebrate species Daphnia magna and Hyalella azteca. The possible use of the rotifers Brachionus calyciflorus and Brachionus havanensis with the ECOTOX system is also assessed. Findings indicate that at the present state ECOTOX and DaphniaTox are not suitable for inclusion in an early-warning system, but based on visual observation the parameters measured are sensitive to the contaminants tested and consistent, and with suggested modifications these systems have the potential to be fitting additions in an early-warning system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".