Bibliographic record
Abstract
Proteins play important biological functions and are commonly associated with a variety of diseases. One such protein is tau protein, which maintains brain cell function and is linked to neurodegeneration. The complex tau protein biochemistry is composed of the post-translational modifications, interactions with binding partners and aggregation, among other pathways. To investigate the complex biochemistry of tau protein, we utilized electrochemical methods (cyclic voltammetry and electrochemical impedance spectroscopy. We demonstrated detection of protein-protein interactions (1), protein-ligand interactions (2), enzymatic catalysis and enzyme inhibition (3). For this purpose, tau protein film on Au surface was fabricated and characterized. Tau-Au films were used to probe interactions with heparin, ferritin, transferrin, antibodies, and protein kinases. Our data indicate that tau-Au films are functional surfaces which allow for monitoring biomolecular interactions, and enzymatic transformations. References (1) a) Carlin, N., Martic-Milne (2018) J. Electrochem. Soc. 165: G3018-G3025. b) Jahshan, A., Esteves, J.O., Martic-Milne (2016) J. Inorg. Biochem. 162: 127-134. (2) Trzeciakiewicz, H., Esteves, J. O.V., Carlin, N., Martic, S. (2015) Electrochim. Acta 162: 24-30. (3) Esteves, J.O.V., Martic-Milne, S. (2016) Anal. Biochem. 496: 55-62.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".