Leaf Area Estimation in Chamomile
Bibliographic record
Abstract
The knowledge of the variables specific leaf area and leaf area index is important for direct or indirect quantification of plant growth, development and yield. However, there is a lack of these information due to the difficulty in measuring the leaf area of chamomile. Measuring leaf area by direct methods, such as the use of leaf area integrator is a very laborious and time consuming activity because the plant has many leaves and with small size. The use of leaf dry matter is a promising variable for the leaf area estimation. As an important measure to evaluate plant growth, the present study aimed to obtain a model for chamomile leaf area estimation through leaf dry matter. The experiment was conducted in two sowing dates (March 18 and June 30, 2017) at different plant densities (66, 33, 22, 16, 13, 11 and 8 plants m-2). The leaves of chamomile plants were collected in the plant vegetative and reproductive phases. The leaf area determination was performed using the electronic integration method of leaf area. The specific leaf area was 133 cm2 g-1, with no differences between sowing dates, plant densities and phenological phases of plant collection. The leaf area measured with the electronic leaf area integrator exhibited high correlation with chamomile leaf dry matter and the resulting model of leaf area data by the integrator presented optimum performance. This model is indicated for leaf area determination of chamomile when there is availability of leaf dry matter 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 | 0.001 | 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 | 0.001 |
| 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".