Bibliographic record
Abstract
In order to strengthen the germplasm collection and conservation of special oil crops,and offer the service for breeding research and utilization expediently,the status of germplasm conservation for special oil crops in China and some important countries were illuminated in this study.13 countries such as America,India,Europe on Union and China and so on,hold almost 90000 germplasm accessions of special oil crops including more than 30000 flax accessions,over 21800 sunflower accessions,more 15000 safflower accessions,about 5000 castor bean accessions and approximately 900 perilla accessions.Most flax resources are conserved in America,Russia,Canada and Europe on Union;sunflower germplasm accessions are mainly collected in America,Europe on Union and China;large numbers of safflower accessions are distributed in India,America,China and Russia;and most castor bean resources are kept in China,America and India.As for the accession numbers of special oil crops among those countries,America ranks first which possesses more than 22000 accessions,India ranks second,and Europe on Union,China and Russia are in the middle.8400 accessions of special oil crops(castor bean,sunflower,safflower and Perilla)are conserved in China,21% of which are foreign germplasms,and most of native germplasms come from Hubei Province,North China,Northeast,Northwest and Southwest.This study is valuable for China germplasm introduction,collection and preservation of special oil crops,and it not only point out the direction,but also provide the reference.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".