Computed tomography scanning for three-dimensional imaging and complexity analysis of developing root systems
Bibliographic record
Abstract
To improve our understanding of the role of root systems in soil-based resource acquisition by plants and eventually model it completely, root system complexity must be quantified, in addition to other morphometric traits. In this note, we introduce a new approach in which computed tomography (CT) scan data are collected on crop root systems in three-dimensional (3-D) space nondestructively and noninvasively, thus allowing for repeated measurements and a relevant complexity analysis of root systems. The experimental crop is maize ( Zea mays L.). Four potted seedlings were CT scanned under wet soil conditions on the day of emergence, and each of the two following days. Specifically, a high-resolution X-ray CT scanner formerly used for medical purposes produced 3 × 500 CT images of 0.1 mm thick cross-sections for each seedling. The fractal dimension of each root system on each day was estimated on a skeletonized 3-D image reconstructed from CT scan data. We found that the mean fractal dimension value was not significantly greater than 1 on day 1 (1.015 ± 0.015), contrary to days 2 and 3 (1.037 ± 0.015, 1.065 ± 0.016). Our results, including original 3-D images, provide support for a novel type of root system studies based on the collection and advanced analysis of CT scan data.
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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 | 0.000 | 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) | 0.000 | 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".