Spatial variability of cadmium, copper, manganese, nickel and zinc in the Port Curtis Estuary, Queensland, Australia
Bibliographic record
Abstract
Port Curtis is a rapidly growing industrialised and urbanised harbour in Central Queensland, Australia. The spatial variability of trace metals in waters and suspended particulates was determined along axial transects within the harbour and in oceanic waters adjacent to Port Curtis. Dissolved metal concentrations were significantly elevated in Port Curtis compared with the concentrations measured in the adjacent coastal waters. Dissolved copper and zinc concentrations ranged from <19 to 800 and <31 to 580 ng L–1, respectively, and maxima were observed in inner harbour waters adjacent to the southern entrance to the Narrows and in close proximity to anthropogenic sources. Dissolved nickel concentrations were measured in the range of 110 to 900 ng L–1, and exhibited a maximum concentration in the central to northern Narrows, in an area that was not adjacent to anthropogenic sources. Dissolved manganese concentration maxima were measured in close proximity to the dissolved nickel maxima. It appears likely that the elevated dissolved metal concentrations in Port Curtis and the Narrows were not caused by a single point source, and are the result of several factors, including industrial activity around the foreshore, fluxes from sediment-porewater, low flushing durations, lower water pH and possibly episodic inputs from adjacent rivers.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 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".