Speciation of organotin compounds in sediment cores from Guanabara Bay, Rio de Janeiro (Brazil) by gas chromatography–pulsed flame photometric detection
Bibliographic record
Abstract
Abstract The contamination of sediments by organotins poses a threat to marine biota that may last long after release of the substances. The determination of tributyltin (TBT) and its decay products in sediment cores allows elucidation of concentration and degradation trends, and is a useful tool to support management decisions. In this study, organotin speciation was performed on cores from several locations in Guanabara Bay, Rio de Janeiro, to investigate contamination trends over the last 30 years in this area, which houses the second most important harbor in Brazil. TBT concentration in surface sediments ranged from 742 µg kg−1 (as tin) in the vicinity of a major shipyard to 14 µg kg−1 (as tin) in an environmental protection area. Organotins depth profiles were, in general, very irregular, lacking evidence that TBT degradation occurs at appreciable rates in these anoxic sediments. Decay most probably takes place predominantly in the water column and at the water–sediment interface before final burial in the sediments. Data from the least contaminated area was used to estimate a first‐order degradation constant of −0.37 years−1 for dibutyltin. Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".