Slow-Dissociation and Slow-Recombination Assumptions in Nonequilibrium Capillary Electrophoresis of Equilibrium Mixtures
Bibliographic record
Abstract
Nonequilibrium capillary electrophoresis of equilibrium mixtures (NECEEM) is a kinetic affinity method with both analytical and preparative applications. NECEEM requires that the dissociation of the complexes be negligible in its first phase and the recombination of the dissociated complexes be negligible in its second phase. Here, we introduce a method, which facilitates easy examination of whether or not these requirements are satisfied. We derived expressions for two parameters, termed the slow-dissociation parameter (SDP) and slow-recombination parameter (SRP), which can be used to assess the assumptions. Both parameters should be much less than 1 for the assumptions to be satisfied. We calculated the two parameters for new and previously published NECEEM experiments and found that the assumptions were satisfied in all of them. Finally, we discuss changes to NECEEM conditions that should be done if the assumptions are found not to be satisfied. The SDP/SRP assessment helps to easily validate the results of NECEEM-based analyses and thus makes the NECEEM method more robust.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".