Toshiyuki Fukao
Bibliographic record
Abstract
Toshiyuki Fukao died suddenly on February 11, 2020, of cerebral hemorrhage. He received his MD degree from Mie University and started clinical training at Gifu University School of Medicine. He worked from 1988 to 1990 at Shinshu University School of Medicine in the laboratory of Professor Takashi Hashimoto, where he conducted molecular studies of beta-ketothiolase (BKT) and became interested in fatty acid and ketone body metabolism. He received his PhD degree at Gifu, under the supervision of Professor Tadao Orii and of Seiji Yamaguchi (then an Associate Professor). Throughout his career, his research centered on improving the diagnosis and treatment of inborn errors of lipid energy metabolism. His laboratory became a world center for the diagnosis of inborn errors of ketone body metabolism including beta-ketothiolase deficiency. In 2013, he was appointed Professor of the Department of Pediatrics, Graduate School of Medicine at Gifu University. There he worked to advance many areas of research and clinical expertise. He lectured throughout Asia on inborn errors of metabolism and developed a broad international collaborative network. He contributed actively to the annual SSIEM meetings and to the INFORM meetings about fatty acid and ketone body metabolism. At the time of his death, Professor Fukao was serving as President of the Japanese Society for Inherited Metabolic Diseases. He was organizing the ICIEM 2025 meeting, to be held in Japan and of which he would have been President. He was a devoted colleague, mentor and friend. To his family we extend our deepest sympathy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.103 | 0.038 |
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".