Bibliographic record
Abstract
The PLant ANImation (PLANI) framework allows a designer's ideas and decisions about virtual plants to be guided through a structured process that results in an animation of a plant.The process proceeds by selecting relevant objects with properties from four logically grouped domains to simplify implementation.The resulting grouped objects are used as the baseline parameters for the coding process to create the virtual plant.PLANI's construction is based on more than a thousand years of biological research, fifty years of functional-structural plant modelling, and ten years of ontology development, instantiated into an animation environment.PLANI ensures that, when designing virtual plants, a selection of objects derived from an appropriate ontology are considered, and that this selection depends on the purpose of the animation, e.g., whether it is for gaming animation, biological simulation, or film animation.The use of PLANI provides the developer with a framework that is flexible, covers a wide variety of structural, functional, and animation objects for plants, and provides classification of current computer algorithms by their applications to designing virtual plants.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.048 | 0.016 |
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".