A novel fluidized bed respirometric technique for determination of<i>in situ</i>biofilm kinetics
Bibliographic record
Abstract
A respirometric approach has been developed to determine heterotrophic biofilm kinetics using fluidized bioparticles--particles with attached biomass. Lava rock particles of 600 microm were used as a biomass carrier medium. The modified respirometer successfully estimates in situ biofilm kinetics of the bioparticles collected from a pilot-scale liquid-solid circulating fluidized bed (LSCFB) bioreactor. The observed maximum specific growth rates (micro(max)) of 3.69 +/- 0.44 d(-1) and biomass yields (Y(H)) of 0.36 +/- 0.03 g COD/g COD in the fluidized bed respirometers were significantly different from the micro(max) of 5.57-5.72 d(-1) and Y(H) of 0.54-0.59 g COD/g COD observed in the conventional respirometric tests for bioparticles and detached biomass. The higher Monod half-saturation coefficient (K(S)) of 186-219mg COD/L observed in the fluidized bed respirometers relative to the 49-58 mg COD/L in the conventional respirometers reveals the presence of mass transfer resistance in the LSCFB despite fluidization. Significantly reduced yields in the fluidized bed respirometers and the estimated maintenance coefficient of 1.16 d(-1) for the particulate biofilm in the LSCFB clearly emphasize that a substantial amount of substrate was utilized for cell maintenance at the low food to microorganism (S/X) ratio of 0.5 g COD/g VSS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".