Bibliographic record
Abstract
Consolato M. Sergi, MD, PhD, MPH, FRCPC, FCAP, is chief of pathology at the Children’s Hospital of Eastern Ontario, full professor of pathology and an adjunct professor of pediatrics at the Universities of Ottawa, Ontario, and Alberta, Canada. He is also a consultant for Standards and Guidelines in Carcinogenesis of Chemical Compounds published by the World Health Organization/International Agency on Research on Cancer (WHO/IARC monographs), Lyon, France. His research interests include hepatic tumors, metabolic diseases, cholangiopathies, organ transplantation, and gut/bile microbiome using cell lines, animal models, and clinical samples. He identified the role of apoptosis in ductal plate malformation of the liver, characterized sialidosis, and found two new genes, WDR62, which encodes a centrosome-associated protein (Nat Genet 2010) and OTX2, mutations of which can contribute to dysgnathia (J Med Genet 2012). Professor Sergi has published more than 350 research/review articles and several books and book chapters. All the royalties from his books go to charities of families and children. He has supervised and mentored many PhD students and clinical fellows. He is also on the editorial boards of several scientific journals.
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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.208 | 0.127 |
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".