A simple and rapid method for measuring total free sulfides in marine sediments
Bibliographic record
Abstract
Abstract The quantitatively most important process by which organic matter in marine sediments is mineralized is performed by sulfate‐reducing bacteria, resulting in the accumulation of total dissolved (free) sulfide (S2− = H2S + HS− + S2−) in porewater. S2− is toxic to benthic animals and vascular plants and measurements serve as a proxy for the deleterious effects of organic enrichment on benthic habitat, biodiversity, and ecosystem function. Methodologies for measuring S2− in water have been pursued for at least a century, and standard approaches employ colorimetry (methylene blue and iodometric titration) and potentiometry. These standard methods require between 1 and 200 mL of porewater, which can be laborious to obtain. The ion‐selective electrode method is widely employed as a practical approach for sediment S2− analysis but lacks analytical robustness and is highly prone to measurement biases that misinform research and environmental management decisions. A technically simple method is described, based on direct UV spectrophotometry, for the near real‐time field analysis of small porewater samples. The procedure prevents known measurement biases associated with particulate sulfide interference, S2− volatilization and oxidation, and represents a practical approach for monitoring organic enrichment and classifying benthic ecological quality status. Porewater concentrations between 200 and 15,000 μmol L−1 can be measured and instrument calibration is highly stable. The method has the capacity to rapidly process and analyze sediment samples at low cost, which helps resolve the problem of chronic under‐sampling associated with the use of traditional S2− methods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".