Ceilometer Measurements from The University of Western Ontario of Smoke from the Extraordinary Fires of 2017 in Western Canada
Bibliographic record
Abstract
Background: The summer of 2017 saw many fires in Western Canada. Smoke from these fires was transported by winds over to London and was measured using a Lufft CHM15k ceilometer which was installed at the Cronyn Observatory of The University of Western Ontario. Methods: The cloud base height can be calculated by the time taken for the backscatter signal to reach the transmitter while the backscatter effects can be used to determine the atmospheric structure using the principle of light detection and ranging (LiDAR). Results: Smoke particle concentrations over London, Ontario were observed within 72 hours of the fires taking place in the west. The smoke plumes were frequently visible from late May to late October 2017 with smoke concentrations peaking between August and September. Discussion and Conclusion: Our measurements will help to validate estimates of smoke dispersal from the fire sources by testing whether transport predictions match both the London Canada as well as the European measurements. Interdisciplinary Reflection: The ceilometer activity aims at developing the capability to make continuous measurements of forest fire smoke, volcanic ash and/or smoke plumes which can affect aviation traffic and cause health and safety risks.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".