Quantification of the viscoelasticity of the bond of biotic and abiotic particles adhering to solid-liquid interfaces using a window-equipped quartz crystal microbalance with dissipation
Bibliographic record
Abstract
The quartz-crystal-microbalance-with-dissipation (QCM-D) has become a powerful tool for studying the bond viscoelasticity of biotic and abiotic colloidal particles adhering to substratum surfaces. A window-equipped QCM-D allows high-throughput analysis of the average bond viscoelasticity , measuring over 10 6 particles simultaneously in one single experiment. Other techniques require laborious analyses of individual particles. In this protocol, the quantitative derivation of the spring-constant and drag-coefficient of the bond between adhering colloidal particles and substratum surfaces using QCM-D is explained for bacteria and silica particles, using the particle-mass derived for validation. Bond viscoelasticity is calculated using a coupled resonator model, paying special attention to the protocol for mathematical fitting needed to obtain reliable quantitative output. Knowledge of the viscoelasticity of the bond between colloidal particles and substratum surfaces facilitates development of new strategies to detach adhering particles from or retain them on a surface.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".