Are Active Fluids Age-Dependent?
Bibliographic record
Abstract
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".