A comparison of the fragmentation pathways of [Cu <sup>II</sup> (M <sub>a</sub> )(M <sub>b</sub> )] <sup>•2+</sup> complexes where M <sub>a</sub> and M <sub>b</sub> are peptides containing either a tryptophan or a tyrosine residue
Bibliographic record
Abstract
[Cu(II)(M(a))(M(b))](•2+) complexes, where M(a) and M(b) are dipeptides or tripeptides each containing either a tryptophan (W) or tyrosine (Y) residue, have been examined by means of electrospray tandem mass spectrometry. Collision-induced dissociations (CIDs) of complexes containing identical peptides having a tryptophan residue generated abundant radical cations of the peptides; by contrast, for complexes containing peptides having a tyrosine residue, the main fragmentation channel is dissociative proton transfer to give [M(a) + H](+) and [Cu(II)(M(b)-H)](•+). When there are two different peptides in the complex, each containing a tryptophan residue, radical cations are again the major products, with their relative abundances depending on the locations of the tryptophan residue in the peptides. In the CIDs of mixed complexes, where one peptide contains a tryptophan residue and the other a tyrosine residue, the main fragmentation channel is formation of the radical cation of the tryptophan-containing peptide and not proton transfer from the tyrosine-containing peptide to give a protonated peptide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".