Trace metals in the sponge<i>Ircinia felix</i>and sediments from north‐western Trinidad, West Indies
Bibliographic record
Abstract
The purpose of this study was to obtain data for trace metals in the sponge, Ircinia felix, and sediments found in coastal areas of north-western Trinidad, and to determine whether this sponge could be useful as a biomonitor for selected metals. Three sets of sediment and tissue samples were collected from four stations representing a range of anthropogenic input over a 12-month period. Samples were analyzed for Cd, Cr, Cu, Ni, Pb and Zn using flame and graphite furnace atomic absorption spectrometry. Extractable metal concentrations in sediments ranged from 0.01-0.28 μg g(-1)-cadmium, 0.02-16.2 μg g(-1)-chromium, 0.19-68.5 μg g(-1)-copper, <0.05-4.12 μg g(-1) -nickel, <0.03-37.0 μg g(-1) -lead and 4.08-148 μg g(-1)-zinc. Total metal concentrations in I. felix tissue (dry weight) ranged from 0.03-1.04 μg g(-1)-cadmium, 2.51-24.9 μg g(-1) -chromium, 15.2-49.9 μg g(-1)-copper, 6.30-53.9 μg g(-1) -nickel, 0.27-35.4 μg g(-1) -lead and 29.7-127 μg g(-1)- zinc. The results of the study suggest that I. felix could potentially have use as a biomonitor for Ni, Cd, Cu, and possibly Cr and Zn but may be less useful for monitoring Pb. Further work on temporal trends and intra-species variation of trace metals in the sponge is recommended.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".