Bibliographic record
Abstract
Atmospheric deposition rates of heavy metals (As, Cd, Co, Cu, Hg, Mn, Ni, Pb, and Zn) were determined from July 2009−December 2010 in downtown Toronto. Atmospheric deposition samples were collected using samplers with plastic, glass and water surfaces from two rooftops (15 m and 59 m above ground) in the city core of Toronto. Mercury species were analyzed using Cold Vapor Atomic Fluorescence Spectrophotometer (CVAFS) and the rest of metals were analyzed by acid digestion combined with Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). The results showed that the deposition of heavy metals was higher on water surface as compared to both the plastic and glass surfaces and that Cu, Mn, Pb and Zn showed higher deposition rates as compared to As, Cd, Co and Ni. The deposition rates were higher on Kerr Hall North (KHN) site indicating contribution from local sources. For total mercury (THg) and methyl mercury (MeHg), the deposition rates were higher on Jorgenson (JOR) site as compared to KHN site.
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 | 0.002 |
| 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) | 0.004 | 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".