Two-dimensional liquid chromatography with reversed phase in both dimensions: A review
Bibliographic record
Abstract
Two-dimensional liquid chromatography (2D-LC), and in particular comprehensive two-dimensional liquid chromatography (LC×LC), offers increased peak capacity, resolution and selectivity compared to one-dimensional liquid chromatography. It is commonly accepted that the technique produces the best results when the separation mechanisms in the two dimensions are completely orthogonal; however, the use of similar separation mechanisms in both dimensions has been gaining popularity as it helps avoid difficulties related to mobile phase incompatibility and poor column efficiency. The remarkable advantages of using reversed phase in both dimensions (RPLC×RPLC) over other separation mechanisms made it a promising technique in the separation of complex samples. This review discusses some physical and practical considerations in method development for 2D-LC involving the use of RP in both dimensions. In addition, an extensive overview is presented of different applications that relied on RPLC×RPLC and 2D-LC with reversed phase column combinations to separate components of complex samples in different fields including food analysis, natural product analysis, environmental analysis, proteomics, lipidomics and metabolomics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".