Survival on land: A dark-grown seedling searching for path
Bibliographic record
Abstract
To initiate its development into a plant, a small dark-grown seedling (prior to its emergence from the ground) must penetrate through the growth media. The path that the seedling takes during this journey has yet to be explained. As such, we conducted non-destructive tests using CT scans to observe the growth of dark-grown seedlings in soil over time; we also developed a model to simulate the dynamics of an emerging seedling, and to examine effects of various growth medium conditions, including Lunar soil. It was previously postulated that, with gravitropism in a terrestrial growth medium, a dark-grown seedling would grow directly upright. However, our CT scan results showed that dark-grown soybean seedlings departed from the vertical path in soil, as far as a lateral distance of approximately 10 mm. The phenomenon of the non-straight path was also demonstrated by the model results. Through simulations, we found that an emerging seedling naturally weaves through the particles of growth medium, in search for the path of least resistance. As a result, the seedling ends up travelling a longer distance. Compared with a seedling that was artificially forced to take a straight path in a growth media, the seedling taking the natural path encountered significantly lower resistances (20% lower) from the growth medium, while travelled 12% longer distance during the emergence process. A seedling encountered a much higher impedance in Lunar soil. Our results suggest that taking the path of least resistance, in addition to shaping and orientating itself for mechanical advantage, are strategies evolved by plant species that have contributed to its vast success. An understanding of plant behavior and survival strategies on Earth lay the foundation for future research in agriculture in novel environments, including on celestial bodies.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".