Bibliographic record
Abstract
It is with sadness that we report the passing of Professor Mirosław J. Mossakowski on December 26, 2001. Professor Mossakowski was a leading figure in neuropathology and neuroscience in Poland. He was born in 1929 in Bereza Kartuska, eastern Poland. He graduated with distinction from the Medical School in Gdansk in 1953. A year later he moved to Warsaw to obtain PhD training under the guidance of Prof. Adam Opalski at the Department of Histopathology of the Central Nervous System, a research unit that eventually evolved into the Department of Neuropathology. A few years later that research unit became the nucleus of the Medical Research Center of the Polish Academy of Sciences, an institute that he founded and headed for more than a quarter of a century. In the early years of his career he also worked at the Neurological Clinic of the Medical School in Warsaw where he specialized in neurology under the guidance of Prof. I. Hausmanowa-Petrusewicz. In 1959 he left for Montreal where he trained with Wilder Penfield at the Montreal Neurological Institute. In 1966 the Medical Academy of Warsaw granted him the Second Doctorate (doctor habilitatus) for his thesis entitled “Pathomorphology and Histochemistry of Spontaneous and Experimental Hepatic Encephalopathies.” The years 1966–1967 were spent working in the laboratory of Professor Igor Klatzo at the National Institutes of Health.
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 | 0.003 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.141 | 0.100 |
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".