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Record W4224115445 · doi:10.34297/ajbsr.2022.15.002129

Effects of Turbulent Mixing and Orbitally Shaking on Cell Growth and Biomass Production in Active Fluids

2022· article· en· W4224115445 on OpenAlex
Hassan Peerhossaini

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

VenueAmerican Journal of Biomedical Science & Research · 2022
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMixing (physics)Biomass (ecology)Yield (engineering)DiffusionTurbulenceMaterials scienceChemistryMolecular diffusionPulp and paper industryEnvironmental scienceChemical engineeringBiological systemMechanicsBiologyThermodynamicsPhysicsEcologyMetallurgy

Abstract

fetched live from OpenAlex

We have previously reported the effects of mixing on bacterial growth. Mixing can be achieved with different methods and in diverse devices. However, the nature of the intimate contact (the main purpose of mixing) made between different substances in a mixing vessel is a strong function of the hydrodynamic that underlies the specific mixing method. This study aimed to compare the growth and biomass yield of cyanobacterium Synechosystis sp. CPCC 534 (as a microorganism model) obtained by three different mixing methods commonly used in life science labs and in the industry, i.e., turbulent stirring (TS), orbital shaking (OS), and simple molecular diffusion (MD). The results revealed that imposing mixing on the culture significantly improved the specific growth rate as well as biomass yield production in comparison with simple molecular diffusion. Mixing obtained by turbulent stirring proved to be more efficient than the one achieved by orbitally shaking, in the production of Chlorophylla (Chla) and phycocyanin (PC). The results of this study can help choosing the appropriate mixing method in life science research.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.134
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.307
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