Gas transfer velocities measured at low wind speed over a lake
Bibliographic record
Abstract
The relationship between gas transfer velocity and wind speed was evaluated at low wind speeds by quantifying the rate of evasion of the deliberate tracer, SF 6 , from a small oligotrophic lake. Several possible relationships between gas transfer velocity and low wind speed were evaluated by using 1‐min‐averaged wind speeds as a measure of the instantaneous wind speed values. Gas transfer velocities in this data set can be estimated virtually equally well by assuming any of three widely used relationships between k 600 and winds referenced to 10‐m height, U 10 : (1) a bilinear dependence with a break in the slope at ~3.7 m s −1 , which resulted in the best fit; (2) a power dependence; and (3) a constant transfer velocity for U 10 < ~3.7 m s −1 , with a linear dependence on wind speed at higher wind speeds. The lack of a unique relationship between transfer velocity and wind speed at low wind speeds suggests that other processes, such as convective cooling, contribute significantly to gas exchange when the wind speeds are low. All three proposed relationships clearly show a strong dependence on wind for winds > 3.7 m s −1 which, coupled with the typical variability in instantaneous wind speeds observed in the field, leads to average transfer velocity estimates that are higher than those predicted for steady wind trends. The transfer velocities predicted by the bilinear steady wind relationship for U 10 < ~3.7 m s −1 are virtually identical to the theoretical predictions for transfer across a smooth surface.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".