Alkali-metal ion catalysis and inhibition in nucleophilic displacement reactions at carbon, phosphorus and sulfur centres. IX.For Part VIII see ref. 1. p-Nitrophenyl diphenyl phosphateElectronic supplementary information (ESI) available: kinetic data for the reaction of p-nitrophenyl diphenyl phosphate with various reagents in differing media. See http://www.rsc.org/suppdata/ob/b2/b208408b/
Bibliographic record
Abstract
We report on the catalytic effects by alkali-metal ions in the ethanolysis of p-nitrophenyl diphenyl phosphate, in continuation of our studies on alkali-metal ion catalysis and inhibition in nucleophilic displacement reactions at carbon, phosphorus and sulfur centres. The following selectivity order of catalytic reactivity was observed for nucleophilic displacement at the phosphorus center with p-nitrophenoxide as leaving group: Li+ > Na+ > K+ > Cs+. A minor reaction pathway with phenoxide leaving was also found. The kobs data have been dissected into reaction pathways by free ions (kEtO) and by ion pairs (kMOEt), with the latter being dominant, in a 4-membered transition-state. Further analysis is given in terms of initial-state and transition-state stabilization by the alkali-metal ions in terms of the Eisenman model (electrostatic interaction vs. desolvation). Results of ab-initio MO calculations are presented based on interaction between M+ and a model bipyramidal phosphorane intermediate and compared with the sulfurane analogue.
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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 | 0.001 |
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".