A Step Closer Towards the Digital Twin of the Plant
Bibliographic record
Abstract
Digital twins can provide vital insights into agricultural products and processes. There have been a lot of documented attempts at digital twins in agriculture. However, majority of these attempts build synthetic models and ignore the temporal dimension of the plant growth. Therefore, the existing models fail to depict actual plant details and growth. Our work replicates the actual growth of a real plant in the digital world by acquiring 3D meshes of the plant at various instants. It focuses on the transition between those acquired meshes by approximating all the consecutive pairs into approximate mesh pairs that have a common topology. The quality of these common approximate mesh pairs is quantitatively measured by an Energy term, which is minimized during the optimization process. Later, the meshes with the common topology are interpolated (morphing) to build the final digital twin of the plant. Experimental results show that the proposed methodology to attain the final morph has the potential to be a vital module, which could be responsible for the visual updates in the digital replica of the digital twin of the plant.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".