Bibliographic record
Abstract
The worldwide exchange of fruits has been facilitated by traders, travelers, sovereigns, conquerors, diplomats, missionaries, and botanists. The beginnings of organized plant exploration date to the Pharaohs of ancient Egypt, who, as early as 2000 bce , brought back exotic trees and plants in their foreign campaigns and illustrated them on their temple walls. Queen Hatshepsut (ca. 1500 bce ) sent out ships to bring back trees from the land of Punt (northeast African coast). The exchange of plants throughout antiquity was a by-product of trade routes between East and West as well as though the campaigns of conquerors including Alexander, the warriors of Islam, Genghis Khan, and the crusades. The age of exploration starting at the end of the 15th century was inspired by the search for a sea route to the spice-rich East. The encounter of Columbus with the Americas brought about an explosive exchange of New World and Old World plants. The rise of science in the 17th and 18th centuries was associated with botanical exploration involving travels and expeditions, including Hans Sloan to the West Indies, James Cunningham to China, Georg Eberhard Rumpf (Rumphius) to the Moluccas, and Sir Joseph Banks to Newfoundland, Labrador, South America Tahiti, New Zealand, Australia, the Malay Archipelago, Hebrides, and Iceland.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".