Human-driven evolution of cultivated plants and the origin of early civilizations: The concept of Neolithic revolution in the works of Nikolai Vavilov
Bibliographic record
Abstract
The concept of centers of origin of cultivated plants (crop biodiversity hotspots) developed by Nikolai Vavilov (1887-1943) is essential for understanding the origin and evolution of human civilization. Vavilov formulated the principles of the Neolithic agricultural revolution and substantiated the basic patterns for the emergence of agricultural civilizations. He established that the center of speciation of the plants that have a potential for cultivation determines the origin of primary civilization. Humans actively performed the selection of plants with valuable properties, which led to the formation of new cultivated species and varieties, while the starting point for such unconsciously human-directed evolution was the presence of potentially useful traits due to the increased genetic diversity in the center of origin. The spreading of agriculturally important cultivars from the center of their origin led to the propagation of beneficial farming technologies over large areas. The establishment of human civilization resulted from the dynamic quasi-symbiotic relationship between humans and domesticated plants and animals, which human-driven evolution became an essential factor for the transformation and dynamics of human societies. In the addendum, we present archive materials on the cooperation of Nikolai Vavilov with the historians and ethnologists from the editorial board of the journal "Novy Vostok" ("Nouvel Orient"). These materials include his letters to Professor Ilya Borozdin.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".