The effect of hydrodynamics on the mass transfer of dissolved inorganic carbon to the freshwater macrophyte Vallisneria americana
Bibliographic record
Abstract
The combined effects of water velocity (U) and dissolved inorganic carbon (DIC) concentration on photosynthesis rates of Vallisneria americana were investigated. The net photosynthesis rate or O2 flux (Jobs) from leaves increased with U from 0.20 ± 0.01 (mean ± standard error) µmol m‐2 s‐1 at U = 0 m s‐1 (i.e., in stagnant water) to 2.1 ± 0.07 µmol m‐2 s‐1 at U = 0.066 m s‐1. The velocity where Jobs was saturated (Usat) was inversely proportional to the DIC concentration ([DIC]) and decreased monotonically from 0.04 ± 0.01 m s‐1 at 0.46 mol m‐3 to 0.006 ± 0.004 m s‐1 at 4.8 mol m‐3. If the net photosynthesis rate and DIC uptake are equal, HCO3‐ uptake rates contributed ≫90% of DIC uptake at all [DIC] at U = 0.005 m s‐1 and contributed less at higher velocities. The proportion of HCO3‐ uptake to DIC uptake decreased linearly with increasing [DIC]. The measured local Sherwood numbers (Shx) and the parameter a (2.24 ± 1.32) for O2 of the equation, Shx = a Rebx Sc0.33 were higher than predicted for a laminar flat plate boundary layer, indicating that physicochemical activity, such as photosynthesis, influenced Shx. The thickness of the measured concentration boundary layer (ΔCBL) and the diffusive sublayer (ΔDSL) were 63% and 70% smaller, respectively, than theoretical values based on hydrodynamic theory. Theoretical hydrodynamic predictions of mass transfer need to account for biological reactions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".