Comment on egusphere-2025-3152
Bibliographic record
Abstract
Abstract. The climate-altering potential of wildfires through their emissions into the stratosphere has only recently been realized following the major wildfire outbreaks in Canada and Australia. The 2023 Canadian wildfire season stood out for its extended burned area and duration, by far exceeded the previous record-breaking events, including the Australian “Black Summer” in terms of the emitted power and pyroCb count with a total number of 142 Canadian pyroCb events over the season. The incessant fire activity all across Canada produced a succession of smoke injections into the lower stratosphere. Here, we use various satellite data sets, airborne and ground-based observations together with chemistry-transport model simulations to show that despite the exceptional vigor of the 2023 Canadian wildfires, the depth of their stratospheric impact was surprisingly shallow and limited to the lowermost stratosphere. Conversely, the incessant fire activity featuring a long succession of moderate-strength pyroCb events, combined with numerous episodes of synoptic-scale smoke uplift through the warm conveyor belt, led to unparalleled levels of pollution at commercial aircraft cruising altitudes throughout the season.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.019 | 0.007 |
| Insufficient payload (model declined to judge) | 0.321 | 0.202 |
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".