Cu(<scp>ii</scp>)-Mediated decomposition of phosphorothionate PS pesticides. Billion-fold acceleration of the methanolysis of fenitrothion promoted by a simple Cu(<scp>ii</scp>)–ligand system
Bibliographic record
Abstract
The kinetics of methanolysis of the title compound (3) were studied in the presence of Cu(2+), introduced as Cu(OTf), in the presence of 0.5-1.0 eq. of methoxide and in the presence of 1.0 eq. of a ligand such as bipyridyl (5), phenanthroline (6) or 1,5,9-triazacyclododecane (4). In all cases the active species involve Cu(2+)((-)OCH(3)). In the case of added strong-binding ligands 5 or 6, a plot of the observed rate constant for methanolysis of 3 vs. [Cu(2+)](total) gives a curved line modelled by a process having a [Cu(2+)](1/2) dependence consistent with an active monomeric species in equilibrium with an inactive dimer i.e.[LCu(2+)((-)OCH(3))](2) <==> 2LCu(2+)((-)OCH(3)). In the case of the added strong binding ligand 4, the plot of the observed rate constant for methanolysis of 3 vs.[Cu(2+)](total) gives a straight line consistent with the catalytically active species being Cu(2+)(OCH(3)) which shows no propensity to form inactive dimers. Turnover experiments where the [3] > [Cu(2+)](total) indicate that the systems are truly catalytic. In the optimum case a catalytic system comprising 1 mM of the complex 4Cu(2+)((-)OCH(3)) catalyzes the methanolysis of 3 with a t(1/2) of approximately 58 s accounting for a 1.7 x 10(9)-fold acceleration relative to the background reaction at near neutral (s)(s)pH (8.75).
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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".