The Characterization of Fine Particulate Matter in Toronto Using Single Particle Mass Spectrometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) was used to obtain mass spectra of individual aerosol particles in the 0.5 – 2 µm size range in downtown Toronto, Canada for one to two month periods during each season of 2007. A modified version of the Adaptive Resonance Theory (ART-2a) clustering algorithm, which clusters particles based on the similarity of their mass spectra, was shown to be more accurate than the existing algorithm and was used to cluster the ambient data. A total of 21 unique particle types were identified and were characterized based on their chemical composition, their size, and their temporal trends and seasonal variations. Potential sources are also discussed. Particles containing trimethylamine (TMA) were also observed and a more detailed investigation of ambient trends in conjunction with a laboratory experiment was performed in order to elucidate conditions for which TMA will be observed in the particle phase in Southern Ontario.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it