Bibliographic record
Abstract
In this thesis I present the modeling language L+C. L+C is a language based on the formalism of L-systems. It has been created to address the need for a formalism that would allow the expression of complex plant models. Current plant models require the components of the model (organs or cells) to include many parameters to describe the state of the model. Also the need to express complex calculations has been addressed. Signal propagation has been traditionally expressed using context-sensitive L-systems. L+C extends the formalism of L-systems by introducing new concepts: derivation direction and new context. These two concepts are the foundation of a new method of propagating signals in plant models: fast information transfer. Fast information transfer is an alternative, faster method of propagating signals in linear and branching structures represented by L-system strings. The L+C modeling language is implemented in a plant modeling program lpfg, which together with cpfg (another L-system-based modeling program developed at the University of Calgary) are the core part of the modeling environment L-studio. iv
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 | 0.000 | 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) | 0.010 | 0.001 |
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; both teacher heads agree on what is shown here.
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".