Bibliographic record
Abstract
Total concentrations of nine potentially toxic heavy metals (Ba, Cd, Cr, Cu, Hg, Mn, Ni, Pb, and Zn) in indoor settled dusts from houses, offices, classrooms, and laboratories in Greater Toronto Area, Canada were determined. Mercury concentrations were determined using cold vapor atomic fluorescence spectroscopy (CVAFS), whereas the concentrations of eight other metals were determined using inductively coupled plasma atomic emission spectroscopy (ICP-AES). The results showed that the highest level of heavy metals was in the laboratory dusts. Metal concentrations (except those for Mn and Zn) in household, office, and classroom dusts were comparable. Cd, Cr, Cu, Ni, and Zn concentrations in the laboratory dusts and Cu and Zn concentrations in household, office, and classroom dusts exceeded the Canadian Soil Guideline. Metal concentrations in the indoor dusts found in this study were, in general, consistent with those reported in literature. Among the metals studied, Cd, Cu, Hg, Pb, and Zn showed the greatest enrichment in the indoor environments relative to their crustal abundances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".