Viscoelastic Modeling with Interfacial slip of a Protein Monolayer Electrode-Adsorbed on an Acoustic Wave Biosensor
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.
Bibliographic record
Abstract
Transverse-shear mode acoustic wave devices have been used as real-time, label-free detectors of conformational shifts in biomolecules on surfaces. However, material changes in the biochemical monolayers and coupling between the substrate and the surrounding liquid make it difficult to isolate the desired signal, so an understanding of these phenomena is required. An important step in this understanding is knowledge of the material properties of the linker layer that attaches a biochemically selective molecule to the gold surface, in our case, neutravidin. With the goal of obtaining material properties for a neutravidin monolayer, for use in future studies, neutravidin adsorption to the gold surface of an acoustic wave biosensor is described as a viscoelastic monolayer using one-dimensional modeling. Neutravidin is described as forming hydrated, viscoelastic monolayers, and slip is allowed at all interfaces. An impedance model is numerically fit to experimental values using a two-parameter minimization algorithm and values for the shear modulus of the neutravidin monolayer, in agreement with literature values for similar proteins, are obtained. Slip is found on the electrode surface prior to neutravidin adsorption. These results will be used for future modeling studies involving this protein as a linker protein.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it