Low metal bioavailability in a contaminated urban site
Bibliographic record
Abstract
Bioavailability of Cd, Cu, Ni, Pb, and Zn in a metal-enriched railway yard in Montréal, Québec, Canada was assessed using metal speciation, plant uptake, and microbial assays. Metal speciation of extracted soil solutions was estimated using the Windmere Humic Aqueous Model. In soil solutions, free Cd, Ni, and Zn ions represented as much as 80%, 72%, and 62%, respectively, of the total dissolved metals. Copper and Pb were strongly bound by dissolved organic matter, and metal-fulvic acid complexes represented as much as 99% of the total dissolved metals. Three field-collected plant species (dandelion, bladder campion, and chicory) varied in their tendency to accumulate metals in either their leaves or roots. Chicory grown in the greenhouse had significantly higher metal bioconcentration factors than wild chicory. Although the site studied is considered to be contaminated, no metal pool, such as free ions or dissolved or total soil metals, consistently predicted metal uptake by potted chicory. Regression analysis revealed that soil total metal concentrations could adequately predict tissue accumulations of Cd, Ni, Pb, and Zn in bladder campion but only Cd and Zn in dandelion. Data from microbial assays also showed that the soil respiration was not affected by the metal contamination, but that nitrification was inhibited for the most contaminated soils. These results indicate that the metal bioavailability in the railway yard is low, but they also suggest that nitrogen cycling may be affected.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".