Bibliographic record
Abstract
In 1961 he defended his Candidate of Science thesis (similar to PhD degree) on oat variety resistance to loose smut.Cereal smuts were the most important topic in his research besides cereal rusts.He cooperated in the development of anaerobic seed treatment of barley against loose smut and in the study of the physiological mechanism of such treatment.In 1983 he defended his Doctor of Science thesis on genetics of wheat resistance to leaf and stem rust and genetic variability of these rusts.Since the very beginning of his research career he tried to transfer results of his research to wheat breeding by means of cooperation with wheat breeders.He tested breeding materials, supplied the inoculum for tests and participated in cereal breeders' workshops.This fruitful cooperation led to his co-authorship of 14 wheat cultivars.During his post-doctor fellowship in Winnipeg he determined rust resistance genes in East European wheat cultivars unknown till then and studied the mechanism of variability in cereal rusts.His papers on the translocation 1Bl.1RS later widely used in wheat breeding belong to the first ones on this topic.Also his stay in Wageningen was devoted to the yellow rust resistance of wheat cultivars carrying the translocation 1BL.1RS.His contacts with foreign specialists in wheat rusts research contributed to the location of the Cereal Rusts Conference in 1972 to Prague.As a member of the Committee of the European and Mediterranean Cereal Rusts and Powdery Mildew Foundation he helped to develop scientific contacts of East European rust specialists with their colleagues in the West.The laboratory led by him was declared an international cereal rust laboratory in the framework of the East European cooperation on cereal disease resistance.Later on he participated in the COST action 817 as a coordinator of the wheat leaf rust research.With his colleagues he organized the international conference of this action "Approaches to improving disease resistance to meet future needs: airborne pathogens of wheat and barley" in 1997 in Prague.He is author or co-author of more than 300 scientific papers published in domestic and foreign journals and 10 books or university textbooks.He was also active as external teacher in postgraduate university courses and supervisor of domestic and also foreign PhD students.In this activity he took advantage of his broad knowledge of foreign languages that he also applied in translations of technical literature.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.206 | 0.182 |
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".