Determination of Leaf Area Index in Agricultural Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Leaf area index (LAI) remains one of the most important surface state variables required for a complete understanding of many agricultural and meteorological processes (crop growth, gas exchange, energy and water balance, etc.). LAI is also essential for understanding economic yields and plant disease infestations and in providing the linkages between scales (plant, canopy, region). This chapter summarizes the techniques used to measure LAI. It provides examples of direct LAI measurement, a review of the equipment developed for indirect LAI estimation and some approaches used in remote sensing applications. Direct techniques may either be in situ or destructive but are measurements on the leaves themselves. Indirect techniques represent a variety of hand-held optical sensors that infer LAI from measurements of the transmission of radiation through the canopy. For remote sensing, detection relies on the measurement of canopy reflectance from airborne or satellite platforms.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it