[Development and application of the plant phenomics analysis platform].
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the completion of the whole genome sequencing of major important crops, researchers have an increasing demand for high-throughput, accurate and nondestructive phenotyping technologies. The Plant Phenomics Analysis Platform (PPAP) was established in 2017 at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. The platform has the most up-to-date comprehensive phenotyping analysis facility in China with a full spectrum of imaging systems consisting of eight units including visible light, infrared, near-infrared, root near-infrared, fluorescence, chlorophyll fluorescence, high spectral and lidar imaging. The platform has also specifically established phenotyping technologies for complex traits, such as root phenotype collection and analysis, spike and spikelet feature collection and analysis and responses under stress conditions. PPAP is dedicated to providing all-possible services for domestic and international academic communities and industrial partners engaged in plant sciences.
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.
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 it