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Record W4312295308 · doi:10.1115/fedsm2022-87914

Are Active Fluids Age-Dependent?

2022· article· en· W4312295308 on OpenAlexaff
Zahra Samadi, Malihe Mehdizadeh Allaf, Thomas Vourc’h, Christopher T. DeGroot, Hassan Peerhossaini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsWestern University
Fundersnot available
KeywordsMotilityVideo microscopyExponential growthActive matterBiophysicsBacterial growthBiological systemDiffusionBacteriaBiologyChemistryMaterials scienceCell biologyPhysics

Abstract

fetched live from OpenAlex

Abstract Active fluids are often is known as the aqueous suspensions of self-propelled elements such as bacteria, algae, or sperm cells, which their properties fundamentally differ from conventional fluids. Active fluids exhibit remarkable physical manifestations over a wide range of scales, from time-dependent microscopic diffusion to the large-scale colonization of aqueous spaces. Properties of active fluids depend on the behavior of microbial suspensions, among which motility plays a crucial role. In this work, we focus on the effect of microbial growth and aging on microorganism motility. Hence, the motility behavior of cyanobacterium Synechocystis sp. CPCC 534, and its relationship with aging were investigated in a closed microfluidic chip. The growth of Synechocystis cultures was followed from the lag phase, through exponential and linear growth up to the stationary phase. Culture samples were periodically examined; cell populations were measured by spectroscopy technique and cell trajectories were tracked by video-microscopy. Cell trajectory length and average cell motility were extracted from the video recordings and were correlated with the age and growth phase of the bacterium.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.986

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)0.0150.000

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 head0.013
GPT teacher head0.234
Teacher spread0.220 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2022
Admission routes1
Has abstractyes

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