Bibliographic record
Abstract
All articles of this category Introduction Triphenylcarbenium tetrafluoroborate, also called trityl fluoroborate, is widely applied in organic reactions, [ ¹ ] such as dehydrogenation, [ ² ] deprotection of ketone acetals, [ ³ ] alkyl ethers, [ 4 ] oxidation of silyl enol ethers, [ 5 ] preparation of cationic organometallics [ 6 ] or organic complexes, [ 7 ] as a polymerization catalyst [ 8 ] and as a Lewis acid catalyst. [ 9 ] Trityl fluoroborate is a yellow solid (mp 200 ˚C dec.), which is soluble in most organic solvents, e.g., dichloromethane, tetrahydrofuran, and reacts with nucleophilic solvents, e.g., water. Several preparation methods were described in the literature as early as the 1940s. Dauben et al. used triphenylcarbinol and 48% fluoroboric acid, while removing water from the reaction mixture by adding acetic anhydride. [ ¹0a ] In 1972, Olah et al. developed a more convenient and economical route using trityl chloride and anhydrous tetrafluoroboric acid dimethyl etherate in dry benzene. [ ¹0b ] Scheme 1 Improved multi-gram preparation of trityl fluoroborate
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".