A new mixed‐mode model for interpreting and predicting protein elution during isoelectric chromatofocusing
Bibliographic record
Abstract
Experimental data are combined with classic theories describing electrolytes in solution and at surfaces to define the primary mechanisms influencing protein retention and elution during isoelectric chromatofocusing (ICF) of proteins and protein mixtures. Those fundamental findings are used to derive a new model to understand and predict elution times of proteins during ICF. The model uses a modified form of the steric mass action (SMA) isotherm to account for both ion exchange and isoelectric focusing contributions to protein partitioning. The dependence of partitioning on pH is accounted for through the characteristic charge parameter m of the SMA isotherm and the application of Gouy-Chapman theory to define the dependence of the equilibrium binding constant Kbi on both m and ionic strength. Finally, the effects of changes in matrix surface pH on protein retention are quantified through a Donnan equilibrium type model. By accounting for isoelectric focusing, ion binding and exchange, and surface pH contributions to protein retention and elution, the model is shown to accurately capture the dependence of protein elution times on column operating conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".