Three-dimensional visualization in situ and complexity analysis of crop root systems using CT scan data : a primer
Bibliographic record
Abstract
The importance of root systems for soil-based resource acquisition by plants has long motivated researchers to quantify the complexity of root system structures. However, most of those studies proceeded from 2-D spatial data, and thus lacked the relevance of a 3-D analysis. In this project, helical CT scanning was applied to study root systems with an unprecedented level of accuracy, using non-destructive and non-invasive 3-D imaging that allowed for a spatio-temporal analysis. The appropriate CT scan parameters and configuration were determined for root systems of maize seedlings grown in sand and loamy sand. It was found that the soil conditions allowing for better visualization were sand before watering and loamy sand after watering. Root systems were CT scanned and visualized either at a single moment in time or repeatedly on successive days. Complexity analysis was performed by estimating the fractal dimension on skeletonized 3-D images of root systems.
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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 | 0.002 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.050 | 0.020 |
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".