C–N Ring Construction: The Harrity Synthesis of Quinolizidine (–)-217A
Bibliographic record
Abstract
David M. Jenkins of the University of Tennessee devised (J. Am. Chem. Soc. 2011, 133, 19342) an iron catalyst for the aziridination of an alkene 1 with an aryl azide 2. Yoshiji Takemoto of Kyoto University cyclized (Org. Lett. 2011, 13, 6374) the prochiral oxime derivative 4 to the azirine 5 in high ee. Organometallics added to 5 syn to the pendant ester. Hyeung-geun Park of Seoul National University used (Adv. Synth. Catal. 2011, 353, 3313) a chiral phase transfer catalyst to effect the enantioselective alkylation of 6 to 7. Yian Shi of Colorado State University showed (Org. Lett. 2011, 13, 6350) that a chiral Brønsted acid mediated the enantioselective cyclization of 8 to 9. Mattie S.M. Timmer of Victoria University of Wellington and Bridget L. Stocker of Malaghan Institute of Medical Research effected (J. Org. Chem. 2011, 76, 9611) the oxidative cyclization of 10 to 11. They also showed (Tetrahedron Lett. 2011, 52, 4803, not illustrated) that the same cyclization worked well to construct piperidine derivatives. Jose L. Vicario of the Universidad del País Vasco extended (Adv. Synth. Catal. 2011, 353, 3307) organocatalysis to the condensation of 12 with 13 to give the pyrrolidine 14. Jinxing Ye of the East China University of Science and Technology used (Adv. Synth. Catal. 2011, 353, 343) the same Hayashi catalyst to condense 15 with 16 to give 17. André B. Charette of the Université de Montreal expanded (Org. Lett. 2011, 13, 3830) 18, prepared by Petasis-Mannich coupling followed by ring-closing metathesis, to the piperidine 20. Marco Bella of the “Sapienza” University of Roma effected (Org. Lett. 2011, 13, 4546) enantioselective addition of 22 to the prochiral 21 to give 23. Ying-Chun Chen of Sichuan University and Chun-An Fan of Lanzhou University cyclized (Adv. Synth. Catal. 2011, 353, 2721) 24 to 25 in high ee. Andreas Schmid of TU Dortmund showed (Adv. Synth. Catal. 2011, 353, 2501) that ω-laurolactam hydrolases could be used to cyclize the ester 26, but not the free acid, to the macrolactam 27.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".