Method Development for Determining the Removal of Metals from the Water Column under Transformation/Dissolution Conditions for Chronic Hazard Classification
Bibliographic record
Abstract
An extension of the transformation/dissolution protocol (T/DP) was developed and evaluated as a tool to measure the removal of metals from the water column for chronic aquatic hazard classification. The T/DP extension (T/DP-E) consists of 2 parts: T/DP-E part 1, to measure metal removal from the water column via binding of metals to a substrate and subsequent settling, and T/DP-E part 2, to assess the potential for remobilization of metals following resuspension. The T/DP-E methodology (672-h [28-d] removal period, 1-h resuspension event, and 96-h resettling period) was tested using Cu, Co, and Sr solutions in the presence of a substrate. The metal removal rates varied from rapid removal for Cu to slower rates of removal for Co and Sr. The resuspension event did not trigger any increase in dissolved Cu, Co, or Sr. Additional 96-h experiments were conducted using dissolved Ni, Pb, Zn, and Ag and supported the conclusion that the T/DP-E is sufficiently robust to distinguish removal rates between metals with a wide range of reactivities. The proposed method provides a means to quantify the rate of metal removal from the water column and evaluate remobilization potential in a standardized and reliable way. Environ Toxicol Chem 2019;38:2032-2042. © 2019 SETAC.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".