Directed <i>ortho</i>‐Metalation of <i>O</i>‐Aryl <i>N</i>,<i>N</i>‐Dialkylcarbamates: Methodology, Anionic <i>ortho</i>‐Fries Rearrangement, and Lateral Metalation
Bibliographic record
Abstract
The directed ortho‐lithiation reactions of O‐aryl N,N‐dialkylcarbamates as well as O‐1‐naphthyl and O‐2‐naphthyl N,N‐dialkylcarbamates with sec‐butyllithium/tetramethylethylenediamine (sBuLi/TMEDA) followed by quenching with various electrophiles afford a range of polysubstituted aromatic compounds. If the solutions of the ortho‐lithiated carbamates are warmed to room temperature without the addition of external electrophiles, salicylamide and 1‐ and 2‐hydroxynaphthamide derivatives are formed through anionic ortho‐Fries rearrangements. The relative stabilities and reactivities of different O‐aryl N,N‐dialkylcarbamates were investigated. The lateral metalation of 2‐tolyl carbamates with lithium diisopropylamide (LDA) provides a route to benzo[b]furan‐2(3H)‐ones. Previously reported results are used in a comparison of seven O‐based directed metalation groups in reactions with several electrophiles. The described methodology is useful for the preparation of 1,2,3‐substituted aromatic compounds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".