MétaCan
Menu
Back to cohort
Record W4404902391 · doi:10.1002/mlf2.12147

Measurement of optical density of microbes by multi‐light path transmission method

2024· article· en· W4404902391 on OpenAlexaff
Hongwei Wang, C. Gu, Sujuan Xu, Hongfeng Wang, Zhao Xiaomin, Lichuan Gu

Bibliographic record

VenuemLife · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of British Columbia
FundersNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of ChinaShandong University
KeywordsTransmission (telecommunications)Optical densityPath (computing)Optical pathOpticsMaterials scienceComputer sciencePhysicsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Optical density (OD) is an important indicator of microbial density, and a commonly used variable in growth curves to express the growth of microbial culture. However, OD values show a linear relationship with bacterial concentration only at low concentrations. When the cell density is high, the relationship loses linearity, and serial dilution is needed to obtain readings of better accuracy. Here, we show that measuring OD values using shorter light paths is in close equivalence to measuring OD values of the cell culture with corresponding dilution. By measuring three different light paths simultaneously, accurate OD values can be easily obtained from low to high cell density. Using this method, growth curves of Escherichia coli , Staphylococcus aureus , and Pichia pastoris are measured with higher accuracy. To further simplify the process, an L ‐shaped cuvette and a corresponding turbidimeter are designed specifically for OD value measurement based on the multi‐light path transmission method.

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 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)0.000
metaresearch head score (Gemma)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.571
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.303
Teacher spread0.292 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations16
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuemLifeSame topicAdvanced Fluorescence Microscopy TechniquesFrench-language works237,207