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
In this paper, a theoretical approach of extended Stern model is formulated to represent the electric double layer (EDL) for biochemical as well as biological samples. The existing Stern model is used for several decades to describe the phenomena of electric double layer of electrode/electrolyte interface. In the conventional stern model the double layer which is formed between the electrode and electrolyte interface is described by double layer capacitance. Using the existing Stern model, the equivalent circuit model is not valid for electrical double layer capacitance of electrode/electrolyte interface in β dispersion range. The protein molecules form chemical coupling and chemical adsorption along with classical ionic bonding with gold electrodes. Thus, the compactness of EDL decreases and the double layer capacitance is replaced by a constant phase element (CPE). In the present paper, a three-electrode based ECIS device was used to measure the impedance of various enzymatic solutions for practical realization of theoretical approach. The results obtained from experimental work, were simulated by equivalent circuit simulator, ZsimpWin to validate the extended Stern model by comparing χ2 value. Finally the electrical parameters were extracted and compared for Stern model and extended Stern model. The results obtained by practical experiment and equivalent circuit simulation showed the effectiveness of extended Stern model over Stern model.
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 | 0.000 |
| 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