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Record W2522583774 · doi:10.1039/c6lc01055e

Dynamics of bacterial streamers induced clogging in microfluidic devices

2016· article· en· W2522583774 on OpenAlex

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.

Bibliographic record

VenueLab on a Chip · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
Fundersnot available
KeywordsCloggingMicrofluidicsDynamics (music)NanotechnologyMaterials sciencePhysicsAcoustics

Abstract

fetched live from OpenAlex

Using a microfabricated porous media mimic platform, we investigated the clogging dynamics of bacterial biomass that accumulated in the device due to the formation of bacterial streamers. Particularly, we found the existence of a distinct clogging front which advanced via pronounced 'stick-slip' of the viscoelastic bacterial biomass over the solid surface of the micro pillar. Thus, the streamer, the solid surface, and the background fluidic media defined a clear three-phase front influencing these advancing dynamics. Interestingly, we also found that once the clogging became substantial, contrary to a static homogenous saturation state, the clogged mimic exhibited an instability phenomena marked by localized streamer breakage and failure leading to extended water channels throughout the mimic. These findings have implications for design and fabrication of biomedical devices and membrane-type systems such as porous balloon catheters, porous stents and filtration membranes prone to bacteria induced clogging as well as understanding bacterial growth and proliferation in natural porous media such as soil and rocks.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.390

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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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