Bibliographic record
Abstract
Alexander Nickolaevich Zubritsky is a pathologist of the highest category, a member of the European Society of Pathology, Professor. He was born on March 14, 1949 in Severo-Kurilsk, Sakhalin Region in the family of a military therapist. At age 15, worked as a hospital attendant in a pathology department of a hospital in Sverdlovsk and studied at night school for working youth. In 1974, he graduated the curative and preventive faculty of the Sverdlovsk Medical Institute. In 1974–1975, was an internship in pathological anatomy at the basis of Sverdlovsk Regional Clinical Hospital. In 1977, enrolled in correspondence postgraduate study at the Institute of Human Morphology in Moscow on a specialty “pathological anatomy” under the direction of the Hero of Socialist Labor, Lenin Prize laureate, Academician of AMS USSR Prof. A. I. Strukov. In 1990, he defended his thesis “Quantitative analysis of pathomorphological changes in the right ventricle of the heart in group of patients with chronic nonspecificpulmonary diseases” in the I. M. Sechenov Moscow Medical Academy. In 1990, he became a finalist of the Marvin I. Dunn Award for the best presentation in Cardiology at the meeting of the American College of Chest Physicians in Toronto, etc. Author of the 4 rationalization proposals and more 300 published works as sole author, including 27 books (of which 16 are in paper formats, 11 — in electronic versions), manuals and reference books.
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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.057 |
| Scholarly communication | 0.015 | 0.025 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.021 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".