Cleavage of models for RNA mediated by a diZn(II) complex of bis[1,4- <i>N</i> <sub>1</sub> , <i>N</i> <sub>1</sub> ′(1,5,9-triazacyclododecanyl)]butane in methanol and ethanol
Bibliographic record
Abstract
The cleavage of seven RNA model 2-hydroxypropyl aryl phosphates (1) catalyzed by a dinuclear Zn(II) complex of bis[1,4-N 1 ,N 1 ′(1,5,9-triazacyclododecanyl)]butane (4) was studied in methanol and ethanol at 25 °C under pH controlled conditions. The results are compared with what was reported earlier for the dinuclear Zn(II) complex of the lower homologue bis[1,3-N 1 ,N 1 ′(1,5,9-triazacyclododecanyl)]propane (3). In methanol, the higher homologue exhibits saturation binding with substrates having poor aryloxy leaving groups. With good leaving groups there is an observed linear dependence of k obs versus complex concentration without saturation binding over the catalyst concentration range investigated. In ethanol, strong saturation binding between the active form of the catalyst ((RO – ):Zn(II) 2 :4) and all substrates is observed, the results observed in both solvents being similar to what was reported for the lower (RO – ):Zn(II) 2 :3 homologue. Energetics calculations are presented for the (RO – ):Zn(II) 2 :4-catalyzed cleavage of each substrate in both solvents to assess the catalytic efficiency via the ΔΔG ‡ for catalyst binding a transition state comprising [RO – :1] ‡ or its kinetic equivalent.
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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".