Some comments on the life and publications of Jerzy K. Baksalary (1944-2005)
Bibliographic record
Abstract
Following some biographical information on Jerzy K. Baksalary (1944–2005) and some comments by Tadeusz Calinski, Oskar Maria Baksalary, and Image Editors-in-Chief: Bryan L. Shader and Hans Joachim Werner, this article continues with personal remarks on the life and publications of Jerzy K. Baksalary by R. William Farebrother, Jurgen Gros, Jan Hauke, Radoslaw Kala, Erkki Liski, Xiaoji Liu, Augustyn Markiewicz, Wieslaw Migdalek, Friedrich Pukelsheim, Tarmo Pukkila, Simo Puntanen, C. Radhakrishna Rao, George P.H. Styan, Tomasz Szulc, Yongge Tian, Gotz Trenkler, Julia Volaufova, Haruo Yanai, and Fuzhen Zhang. These remarks are followed by a detailed list of, and some comments on, Jerzy Baksalary’s publications prepared by the editors of this article. Four photographs of Jerzy Baksalary illustrate the article, with three of these also including some of his coauthors, colleagues, and Ph.D. students.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".