On the determination of mass transfer in a concentration boundary layer
Why this work is in the frame
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Bibliographic record
Abstract
The mass transfer of scalar quantities (e.g., O 2 and nutrients) in aquatic environments is an important and complex process involving diffusion and advection. In a flowing environment, concentration boundary layers (CBL) occur above the surfaces of organisms when they are a sink or source of scalars. In this study, we used an O 2 microsensor to profile the O 2 concentrations in the CBL above photosynthesizing freshwater macrophyte ( Vallisneria americana ) leaves that were oriented parallel to the flow in a recirculating flow chamber at 0.5 and 3.3 cm s −1 . Measured O 2 profiles were nonlinear indicating the effect of higher order processes near the surface. O 2 flux ( J obs ) was estimated from these profiles by two nonlinear techniques, hyperbolic tangent and logarithmic models, and the commonly applied linear model. An integrated measurement of O 2 flux ( J int ) for each leaf was also measured independently in a stirred chamber. Whereas J obs determined from the hyperbolic tangent (0.42 ± 0.04 [mean SE] µmol m −2 s −1 ) and linear (0.31 ± 0.04 µmol m −2 s −1 ) models overestimated and underestimated J int (0.37 ± 0.05 µmol m −2 s −1 ), respectively, and were not velocity dependant, the hyperbolic tangent model provided the best fit ( r 2 = 0.88) compared with the linear model ( r 2 = 0.77). In addition, the slope of the regression against J int (1.08 ± 0.06) was closest to 1.00 (i.e., a “perfect” fit). The logarithmic model varied with velocity and overestimated J obs (0.98 ± 0.22 µmol m −2 s −1 at 0.005 m s −1 and 0.90 ± 0.18 µmol m −2 s −1 at 0.033 m s −1 ). These results were confirmed in an analysis of 21 published O 2 concentration profiles measured next to sediments, microbial biofilms, planktonic algae, and epilithic algae. We would, therefore, recommend the hyperbolic tangent model to estimate mass transfer in a CBL.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 it