The Impact of Obstruction on a Model of Competitive Exclusion in Plants
Bibliographic record
Abstract
This study extends an earlier work on an agent based model of competitive exclusion in plants by adding obstructions to a toroidal agent world. The agents are called grid plants, whose genome specifies their pattern of growth and when they make seeds. Seed production is the figure of merit used to assess the success of grid plants. Barriers are found to substantially inhibit seed production, out of proportion to the amount of space they occupy. Two types of barriers are used, ones that occupy productive space in the simulation and ones that block growth between grids of the simulation but occupy no space. Both sorts of barriers are found to inhibit seed production well in excess of the physical space obstructed, nor is fraction of obstruction a strong determinant of the level of inhibition. There is a cooperative effect from both seed mortality and barriers: past some threshold dependent on both, the plants take much longer to achieve exponential growth, if at all. A very strong effect of nonlocal adaptation is apparent in the results, where plants evolved under increasing hardship are initially better adapted, even to other boards, but the effect reverses when evolutionary pressure becomes too high.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".