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Record W2098181147 · doi:10.1109/tnb.2006.880822

Effect of Pore Size on the Calculated Pressure at Biological Cells Pore Wall

2006· article· en· W2098181147 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

VenueIEEE Transactions on NanoBioscience · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsElectric fieldPore water pressureDipoleMaterials scienceSaturation (graph theory)Electric potentialField (mathematics)MechanicsCondensed matter physicsVoltageChemistryPhysicsGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

A transient nonlinear finite-element program has been used to calculate the electric field distribution as a function of time for a spherical cell with a pore in a conducting medium during application of a subnanosecond rise time "step" wave, including the effects of dipolar saturation in the water-based cytoplasm and cell medium. The time-dependent pressure on the pore wall has been computed as a function of time as the system polarizes from the change of the energy in the electric field to the left (inside the pore) and to the right (inside the membrane) of the pore wall. The computations suggest that dipolar saturation, while significant, has little effect on the time-dependent electric field distribution but a substantial effect on the field-induced pore wall pressure. Also, the effect of pore size on both the computed electric field and field-induced pressure was studied. As the pore size increases, a collapse in both the electric field and field-induced pressure has been noticed. This suggests that as the pore size increases, the driving force for further opening the pore is not electrical.

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 score0.013
Threshold uncertainty score0.452

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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