Atmospheric trace gas trends obtained from FTIR column measurements in Toronto, Canada from 2002-2019
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
Abstract Total columns of C 2 H 2 , C 2 H 6 , CH 4 , CH 3 OH, CO, H 2 CO, HCl, HCN, HCOOH, HF, HNO 3 , N 2 O, NH 3 and O 3 were retrieved from 2002-2019 using a Fourier transform infrared (FTIR) spectrometer at the University of Toronto Atmospheric Observatory (TAO). Trends and enhancement events were determined by fitting trended Fourier series, and bootstrapping was used to identify the statistical significance. Trends from 2002 to 2019 (%/year, with 2 σ uncertainties) were found for C 2 H 2 (−1.12 ± 0.30), C 2 H 6 (−0.74 ± 0.73 from 2002–2008 and 1.19 ± 0.27 from 2009–2019), CH 4 (0.26 ± 0.10 from 2002–2008 and 0.41 ± 0.03 from 2009–2019), CO (−0.90 ± 0.07), HCN (−0.51 ± 0.21), HCOOH (−2.15 ± 0.64), HF (0.59 ± 0.11), HNO 3 (0.36 ± 0.13), N 2 O (0.28 ± 0.02), NH 3 (3.56 ± 0.85), and O 3 (0.28 ± 0.19 and −0.05 ± 0.07 for tropospheric and stratospheric columns, respectively). The GEOS-Chem chemical transport model showed that wetland emissions were the largest contributor to CH 4 columns measured at TAO (average relative contribution of 31.7%), and that CH 4 oxidation was a major source of CO (accounting for 30.9%).
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 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 it