Investment in plant research and development bears fruit in China
Bibliographic record
Abstract
Recent rapid progress in plant science and biotechnology in China demonstrates that China's stronger support for funding in plant research and development (R&D) has borne fruit. Chinese groups have contributed major advances in a range of fields, such as rice biology, plant hormone and developmental biology, genomics and evolution, plant genetics and epigenetics, as well as plant biotechnology. Strigolactone studies including those identifying its receptor and dissecting its complex structure and signaling are representative of the recent researches from China at the forefront of the field. These advances are attributable in large part to interdisciplinary studies among scientists from plant science, chemistry, bioinformatics, structural biology, and agronomy. The platforms provided by national facilities facilitate this collaboration. As well, efficient restructuring of the top-down organization of state programs and free exploration of scientists' interests have accelerated achievements by Chinese researchers. Here, we provide a general outline of China's progress in plant R&D to highlight fields in which Chinese research has made significant contributions.
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 | 0.001 | 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".