Modeling the Kinetics of Contaminant Biodegradation by a Mixed Microbial Consortium Based on Carbon Mass Balance
Bibliographic record
Abstract
The fate of contaminant carbon was monitored during aerobic biodegradation in the presence of a mixed indigenous microbial consortium in order to calibrate a microbial-growth-based biokinetic model. The methodology simultaneously monitored mineralization, substrate depletion and microbial population evolution in biomass extract spiked with14C-labeled hexadecane. Hexadecane depletion and hexadecane-degrader population were monitored using sacrificed microcosms by centrifuging the extract so that the supernatant and the residue contained residual hexadecane and microbial population, respectively. This methodology allowed verification of the carbon mass balance (average14C-carbon recovery of 90.33 ± 1.62% for biotic microcosms) and calibration of a biokinetic model. Four biokinetic parameters and three yield coefficients were identified (Haldane kinetic parameters:μS = 1.3639 d-1, Ks = 0.4295 mg-C, KI = 6.6457 mg-C; decay kinetic parameter:μd = 1.3.102 d-1; substrate/biomass, carbon dioxide/ biomass during growth and carbon dioxide/biomass during decay yield coefficients: Ys = 1.5948 mg-C/mg-C, YP g = 0.4554 mg-C/mg-C, YP d = 1.3263 mg-C/mg-C) and compared with the literature data. The methodology can facilitate the identification of biodegradation models by decoupling the intrinsic ability of microorganisms to degrade contaminant from restrictions imposed by limiting conditions.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".