Mirza Gökgöl: Plant Scientist, Seed Collector, Agronomist, Breeder and Archaeo-Botanist
Bibliographic record
Abstract
Mirza (Hacızade) Gökgöl (1897-1981) was an outstanding scientist with multiple talents and he had worked as plant scientist, seed collector, agronomist, plant breeder, botanist and archaeo-botanist. Despite the many challenges, he faced during his education and business life, he made many innovations, published several books and articles in the area of seed science, agronomy, wheat systematic, plant breeding and even archaeo-botany. The purpose of this review article is to recognize and appreciate Mirza Gökgöl’s contributions to the scientific world. After completing his Ph. D. program in Germany, M. Gökgöl established Istanbul Yeşilköy Agricultural Research Station, performed extensive seed collecting missions for landraces and wild relatives of cultivated crops, mainly of cereals, performed characterization and breeding programs with the collected germplasm, contributed to development of Crop Domestication Theory (Gene Centres Theory), published numerous scientific research papers and books on Turkey’s plant genetic resources, highlighting their significance and adverse effects of their likely loss. His publications are still among the mostly credited references in the area of plant genetic resources. Most of the bibliographic information cited here is extracted from his personal file kept at the archive of the Ministry of Agriculture and Forestry, Turkey. Apart from the archival information, I have also referred to members of his family through personal communications, to his publications and all the available published materials about Gökgöl.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.025 |
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".