Application of the Conditional Time-Averaged Gradient method to evaluate dry deposition in the Oil Sands region of Alberta, Canada
Bibliographic record
Abstract
Measurements of gaseous SO2, HNO3 and NH3 deposition fluxes at two remote wet fen field sites in the Alberta Oil Sand Region (Canada) have been performed by a COnditional Time Averaged Gradient system during the summer seasons over 2010-2012. The COTAG system works by measuring the concentration gradient only when the conditions for making flux measurements (sufficient fetch and turbulence) are suitable. In this way, average concentration gradients can be measured over periods of days to weeks. When combined with the average turbulence conditions during the sampling, such average gradients can be used to measure the average gas fluxes. With 6 replicate samplers set at two heights, the gradient system provided significant differences in gas concentrations at the two heights for at least half of the summer season, and showed that for periods where fluxes were measurable, the surface resistance to gas transfer was not significantly different from zero. However, during periods where there was no significant difference in gas concentrations at the two heights, the lack of a significant concentration gradient could result from a significant surface resistance, or could simply be the result of large uncertainties in the measurements at concentrations close to the limit of detection of the method. The COTAG measurements do, however, provide an indication of the range of dry deposition rates for these gases at wet fen sites, for which no other experimental data exist for use in inferential modelling of dry deposition across the region. The data here refer only to the summer season, so the dry deposition rates are only representative of surfaces clear of snow, as at low temperatures during winter, the snow pack coverage will cause deposition rates to be different.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".