Structures and unimolecular chemistry of M(Pro<sub>2</sub>-H)<sup>+</sup>(M = Mg, Ca, Sr, Ba, Mn, Fe, Co, Ni, Cu, Zn) by IRMPD spectroscopy, SORI-CID, and theoretical studies
Bibliographic record
Abstract
M(Pro2-H)(+) complexes were electrosprayed and isolated in an FTICR cell where their unimolecular chemistries and structures were explored using SORI-CID and IRMPD spectroscopy. These experiments were augmented by computational methods such as electronic structure, simulated annealing, and atoms in molecules (AIM) calculations. The unimolecular chemistries of the larger metal cation (Ca(2+), Sr(2+) and Ba(2+)) complexes predominantly involve loss of neutral proline whereas the complexes involving the smaller Mg(2+) and transition metal dications tend to lose small neutral molecules such as water and carbon dioxide. Interestingly, all complexes involving transition metal dications except for Cu(Pro2-H)(+) lose H2 upon collisional or IRMPD activation. IRMPD spectroscopy shows that the intact proline in the transition metal complexes and Cu(Pro2-H)(+) is predominantly canonical (charge solvated) while for the Ca(2+), Sr(2+), and Ba(2+) complexes, proline is in its zwitterionic form. The IRMPD spectra for both Mg(Pro2-H)(+) and Mn(Pro2-H)(+) are concluded to have contributions from both charge-solvated and canonical structures.
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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) | 0.002 | 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".