Flame retardants in urban air: A case study in Toronto targeting distinct source sectors
Bibliographic record
Abstract
). The atmospheric concentrations of given chemical classes also showed a general trend of lower levels in winter as compared to summer months. Statistically significant negative correlations between the natural logarithm of concentrations and inverse of temperature for some OPEs and PBDEs highlighted the role of volatilization from local sources at given sites as primarily influencing their atmospheric concentrations. Overall, this study adds to the current knowledge of urban settings as a major emitter of the chemicals of emerging concern and their replacements, as well as the ongoing problem of phased out PBDEs due to their presence in existing inventories of commercial/recycled products. It is recommended that long-term monitoring programs targeting flame retardants (FRs) include urban sites, which provide an early indicator of effectiveness of control measures of targeted FRs, while at the same time providing information on emission sources and trends of replacement FR chemicals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; both teacher heads agree on what is shown here.
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".