Kinetic Studies of the Reactions of SiC and SiSi Bonds
Bibliographic record
Abstract
This chapter contains sections titled: Introduction Experimental Methods Kinetics and Mechanisms of the Reactions of Silenes Unimolecular Reactions Bimolecular Reactions General Trends Dimerization Nucleophilic Addition Addition of Water and Alcohols Addition of Acetic Acid Addition of Aliphatic Amines Addition of Alkoxysilanes Ene- and [2+2]-addition of Ketones, Aldehydes and Esters Ene-, [2+2]- and [4+2]-cycloaddition of Alkenes and Dienes Other Reactions—Oxygen, Sulphoxides and Halocarbons Solvent Effects on Silene Reactivity Substituent Effects on Silene Reactivity Silenes of the Type (R)MeSiCH2 and Me2SiCHR 1-silaallenes Kinetics and Mechanisms of the Reactions of Disilenes Unimolecular Reactions Bimolecular Reactions Addition of Alcohols and Phenols [2+4]-, [2+2]- and [2+1]-cycloadditions of Dienes, Carbonyl Compounds and Oxygen Conclusions Appendix: Negative Arrhenius Activation Energies References
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".