Theme Issue in Memory to Prof. Jiro Tsuji (1927–2022)
Bibliographic record
Abstract
This reprint is dedicated to Professor Jiro Tsuji, who passed away on April 1st, 2022. He pioneered the discovery of transition metal-catalyzed reactions and showed the general idea of developing these reactions in organic synthesis. Well-known reactions include several types of Pd-catalyzed reactions, e.g., substitutions of allylic substrates based on the stoichiometric reaction of -allyl palladium with carbon nucleophiles; reactions of allyl -keto esters, resulting in allylation, olefin formation, and reduction; reactions of propargylic substrates; and methyl ketone formation from 1-olefins based on the Wacker process of ethylene. It is noteworthy that olefin formation is used as the key step in the industrial synthesis of jasmonate. Other reactions catalyzed by Pd, Ru, and Cu are carbonylation of olefins, dienes, acetylenes, and allyl compounds; decarbonylation of acid chloride and aldehydes; oxidative decomposition of catechol to muconic acid, etc. Tsuji focused on the carboncarbon bond forming reaction from the very beginning of his research. The significance of the reactions found by Tsuji was proven by their widespread adoption in academic and industrial laboratories. Consequently, it is not surprising that Tsuji was honored with the Chemical Society of Japan Award in 1981, the Japanese Medal of Honor with Purple Ribbon in 1994, the Japan Academy Prize in 2004, and the Tetrahedron Prize in 2014. He received Honorary Professor at the Tokyo Institute of Technology.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.144 | 0.117 |
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".