Comparison of Three Techniques Used To Measure Diffusive Gas Exchange from Sheltered Aquatic Surfaces
Bibliographic record
Abstract
Three approaches commonly used to quantify diffusive gas exchange across aquatic surfaces were compared in a densely treed, low-wind environment Diffusive surface fluxes of carbon dioxide (CO2) and methane (CH4) from a small boreal reservoir were estimated using (i) surface water concentrations, the thin boundary layer (TBL) equation, and gas transfer velocities (k) calculated using sulfur hexafluoride (SF6); (ii) surface water concentrations, the TBL equation, and k estimated from wind speed; and (iii) static floating chambers (FCs). Comparisons were made during three different approximately 10-day intervals (August 2000, June and September 2001). CO2 and CH4 fluxes estimated from SF6-derived k were on average 1-3 times greater than those determined from wind-estimated k Overall agreement between FC CO2 and CH4 flux estimates and those based on SF6 and wind speed derived kvalues was much weaker, with FC CO2 and CH4 flux estimates ranging from -9 to 23 times those based on SF6 and wind-estimated k values. Chamber deployment likely enhanced gas transfer through disturbance of the surface boundary layer, and results of this study suggest that caution must be exercised concerning the use of FCs on very still water surfaces. Furthermore, findings of this study contradict the common belief that use of wind speed to approximate k is inappropriate for small bodies of water characterized by low winds and surface obstructions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".