Cyclic Chronopotentiometry as a Detection Tool for Flowing Solution Systems
Bibliographic record
Abstract
Cyclic chronopotentiometry provides a very simple detection method, which may be particularly useful in capillary electrophoresis (CE) and microseparation systems. It has been shown that for disk microelectrodes it is possible to define safe reduction and oxidation currents that would never lead to the formation of H2 or O2 gas bubbles, even if they are applied for an indefinitely long time period. During end-column CE detection, currents passing through the working microelectrode can be completely controlled by the external electronic circuit and they are not affected by the separation current. Consequently, problems created by the offset potential in CE can be completely eliminated. The detection can be accomplished through a variety of different mechanisms; however, generation of the electrode response as a result of analyte adsorption seems to be most common. The method is applicable to many analytes, which do not have to be electroactive. The analytical signal is obtained by monitoring the change in the average electrode potential (calculated for either a cathodic or an anodic half-cycle) caused by an analyte interacting with the electrode. The analytical signal is proportional to the analyte concentration, within a concentration range extending over approximately 2 orders of magnitude.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".