Evaluation of alkali metal binding selectivities of caged aza-crown ether ligands by microelectrospray ionization/quadrupole ion trap mass spectrometry
Bibliographic record
Abstract
Microelectrospray ionization mass spectrometry (MESI-MS) is used to evaluate alkali metal binding selectivities of a variety of macrocyclic compounds. Well-studied crown ethers are used to validate the MESI-MS method. A quantitative correlation between MESI mass spectral ion intensities and solution equilibrium distributions of complexes is obtained for the mixtures containing a single host and different alkali metal guest ions. The MESI-MS method is successfully applied for the determination of the alkali metal binding selectivities of a series of cage-functionalized aza-crown ethers and relevant model compounds in methanol and chloroform solutions. The binding selectivities parallel previous results obtained using conventional spectrophotometric extraction methods. Structural differences in the host compounds, such as the presence of a cage functionality, binding cavity size, and overall flexibility, cause significant changes in the binding selectivities.
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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 | 0.000 | 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) | 0.001 | 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 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".