Synthesis of β-Ketosulfonamides Derived from Amino Acids and Their Conversion to β-Keto-α,α-difluorosulfonamides via Electrophilic Fluorination
Bibliographic record
Abstract
β-Ketosulfonamides derived from Boc or Cbz-protected amino acids bearing hydrophobic side chains were prepared in good to excellent yield by treating N -allyl, N -alkyl methanesulfonamides with n -BuLi, followed by reaction of the resulting carbanion with methyl esters of N -protected l -amino acids. The analogous reaction using the dianion derived from an N -alkyl methanesulfonamide proceeded in much lower yield. Electrophilic fluorination of the β-ketosulfonamides using Selectfluor in the presence of CsF in DMF at room temperature for 15–60 min provided β-keto-α,α-difluorosulfonamides in good to excellent yields. The allyl protecting group could be removed in good yield using cat. Pd(PPh) 3 ) 4 and dimethyl barbituric acid. When the fluorination reaction was performed with Cs 2 CO 3 as base, β-ketosulfonamides derived from Val, Leu or Ile gave the expected β-keto-α,α-difluorosulfonamides, while β-ketosulfonamides derived from Ala, Phe, or hPhe gave the hydrates of the imino β-keto-α,α-difluorosulfonamides.
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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) | 0.000 | 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 | 0.001 |
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".