Bibliographic record
Abstract
Abstract The reactivity of metal fragments MeLi(THF), Me2Mg, Me2Zn and Me3Al with a variety of imine/pyridine ligands was studied by DFT methods. Ligands having at least two such groups in conjugation very effectively accept an electron from a metal–carbon bonding orbital and thus assist alkyl dissociation: the M–Me dissociation free energy ΔGd decreases by about 45 kcal/mol for the Li, Mg and Zn fragments, and by 60–70 kcal/mol for Me3Al. Paths for transfer of an alkyl group to the ligands were also explored. Paths for transfer to ligand carbon atoms were found to have high barriers, and such transfers are instead proposed to proceed via initial M–Me dissociation. Direct alkyl transfer to ligand nitrogen atoms is somewhat easier, and for the most electropositive metal Li such a transfer might compete with radical chemistry. For Dimpy, the most stable products are the C3 and C4 alkylation ones. However, the observed regioselectivity of alkyl transfer (often to Npy or C2) does not correlate with product stability and is likely to be a complicated function of radical stability, steric factors and unpaired electron density distribution. The results illustrate that Dimpy and related ligands should be considered strong, reversible oxidants.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".