Bibliographic record
Abstract
BACKGROUND: Linnaeus developed a robust system for naming plants and a useful, if mechanical, system for classifying them. His binomial nomenclature proved the catalyst for the rapid development of our knowledge of orchids, with his work on the family dating back to 1737 in the first edition of his Genera Plantarum. His first work devoted to orchids, indeed the first monograph of the family, was published in 1740 and formed the basis for his account in Species Plantarum, published in 1753, in which he gave a binomial name to each species. Given the overwhelming number of orchids, he included surprisingly few - only 62 mostly European species - in Species Plantarum, his seminal work on the plants of the world. This reflects the European origin of modern botany and the concentration of extra-European exploration on other matters, such as conquest, gold and useful plants. Nevertheless, the scope of Linnaeus' work is broad, including plants from as far afield as India, Japan, China and the Philippines to the east, and eastern Canada, the West Indies and northern South America to the west. In his later publications he described and named a further 45 orchids, mostly from Europe, South Africa and the tropical Americas. SCOPE: The philosophical basis of Linnaeus' work on orchids is discussed and his contribution to our knowledge of the family assessed. His generic and species concepts are considered in the light of current systematic ideas, but his adoption of binomial nomenclature for all plants is his lasting legacy.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".