Dialysis minipeeper for measuring pore-water metal concentrations in laboratory sediment toxicity and bioavailability tests
Bibliographic record
Abstract
Abstract Whave modifieda classical peeper (dialysiscell)design to create minipeepers that are ofconvenient sze for direct pore-water sampling in laboratory sediment toxicity and bioavailability tests. A series of experiments placing peepers in nickel and zinc solutions, two size fractions of nickel-spiked sand, and two field-collected, nickel-spiked sediments, were conducted to evaluate peeper efficacy in measuring overlying water and pore-water metal concentrations. In water-only experiments, concentrations in the peeper cells were not significantly different from those in the surrounding solution by 48 and 96 h for nickel and zinc, respectively. Peeper cells in the sand experiments equilibrated with the surrounding pore water in ≤120 h. In both trials with natural sediment, peeper equilibrium occurred in ≤48 h. Nickel flux into the peeper cells during the first hour of experimentation showed that the rate of equilibration was initially related to media porosity. In fine sand and natural sediment, equilibration was influenced not only by nickel diffusion into the peeper cells, but also by a decrease in concentrations of nickel in pore water due to sediment sorption and diffusion into overlying water. This shortened the time required to reach equilibrium by reducing the difference between the peeper cell and the surrounding pore-water solution. Overall, minipeepers equilibrated with the surrounding pore water or overlying water within a time period sufficiently short to allow for the use of minipeepers in routine sediment toxicity and metal bioavailablity experiments. Sampling precision using minipeepers was comparable (CV = 10.8 %) to that obtained by conventional sediment centrifugation and filtration (CV = 10.5 %).
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".