Establishing a quantitative link between crystal violet absorbance and biomass in biofilms
Bibliographic record
Abstract
Quantifying biomass is essential for studying biofilms in biomanufacturing, yet widely used assays such as crystal violet (CV) often yield results that are difficult to compare across laboratories due to its reliance on absorbance as a subjective proxy for biomass. To address this, we present a standardized method that calibrates CV absorbance against cellular optical density (OD) and dry cell weight (DCW) using centrifuged planktonic cultures. By establishing a three-way correlation among OD, DCW, and CV absorbance, this simple method allows for quantitative, reproducible, and comparable biomass measurements. Validation across Escherichia coli strains and Rhodopseudomonas palustris showed strong linearity, particularly when using 10% acetic acid as the solvent. Seasonal and instrument-based variability were evaluated, supporting the method’s robustness and broad utility. This method enables researchers to normalize CV data, improving inter-laboratory comparability and supporting more accurate assessment of biofilm productivity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".