The Characteristics of the Dry Deposition Velocity for O<sub>3</sub>regarding Surface Wetness
Bibliographic record
Abstract
It has been researched the relationship between deposition velocity and factors which could affect the deposition phenomena and deposition velocity also has been estimated fer several land-use types. The typical deposition velocities are complex functions of surface types, atmospheric stabilities, friction velocities, air pollutants and so on. The canopy resistance is major contribution to the model's total resistance for O₃. Canopy wetness is also an important factor to calculate deposition velocity. We considered the canopy wetness as canopy water content(CWC) in our Model. But, it is not easy to observe CWC over each land-use types. In this study, we use CWC observed by EMEFS(CANADA Environment Service, 1988) to examine the influence of CWC in estimation of 03 dry deposition velocity(V/sub d/) in summertime. The value of O₃ V/sub d/ range 0.2 ∼ 0.7 cm s/sup -1/ on dry surface and 0.01 ∼ 0.35 cm s/sup -1/ on wet surface in daytime.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".