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Record W4414751343 · doi:10.1016/j.mex.2025.103630

Establishing a quantitative link between crystal violet absorbance and biomass in biofilms

2025· article· en· W4414751343 on OpenAlex
Sheida M. Stephens, Radhakrishnan Mahadevan, D. Grant Allen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMethodsX · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAbsorbanceCrystal violetBiofilmBiomass (ecology)Robustness (evolution)ComparabilityAcetic acid

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.368
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it