Bibliographic record
Abstract
Presented a new approach to the training future teachers, including Science (biology, botany, etc.) through the prism of the rose named after the last pharaoh of Egypt, Queen Cleopatra. The authors consider the Cleopatra rose not through the preparation of a plant in the laboratory (while scientific botanists search to know flowers physiologically and morphologically in the spirit of progress and truth,), but reveal the secrets and magic of the Cleopatra rose through the knowledge of "life truths", thus forming professionally oriented foreign language educational space at university (foreign language, history, geography, philosophy, chemistry, art (A.S. Arensky's ballet "Egyptian Nights", operas "Cléopâtre" by Massenet and "Giulio Cesare in Egitto" by Haendel), cinema, literature, psychology), involving students in romantic love, the ability to understand the flower codes inherent in the Cleopatra rose. We use floral codes strategically in their fiction as subtexts for practitioners of the language of flowers. Key words: Queen Cleopatra, rose Cleopatra,
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".