Development of a biomarker-based index for assessing the ecotoxic potential of aquatic sites
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
The use of biochemical or physiological measurements as indicators of ecotoxicity is under constant development and has the advantage of delineating effects before the appearance of disease. However, these biomarkers are often part of a battery of tests, and it is difficult to integrate them together to gain an overall view of an organism's health. The aim of this study was to develop an index that could integrate the data derived from a battery of biomarkers for application to both spatial and temporal studies. Mya arenaria clams were collected at different sites along the Saguenay Fjord (Quebec, Canada). Six biomarkers were measured: metallothioneins, DNA strand breakage, lipid peroxidation, vitellin-like proteins, phagocytosis, and non-specific esterase activity in haemocytes. A biomarker index was obtained by summing the biomarker values expressed in term of classes. Classes were determined by a distribution-free approach derived from the theory of rough sets. The results of the spatial study show that the index values discriminated well between contaminated and uncontaminated sites. The highly polluted sites had the highest index values (18 compared with a reference value of 14). In the temporal study, the index was also able to highlight possible contamination-induced alterations, even though the interpretation of temporal variation is complicated by natural variations occurring throughout the year. A control chart approach is proposed for determining contaminated sites in both spatial and temporal surveys.
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.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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