LAI Measurements in White Beans and Corn Canopies with Two Optical Instruments
Bibliographic record
Abstract
Leaf Area Index (LAI) is a parameter used to describe the percentage of vegetation cover and to estimate productivity or yield of agriculture and forest canopies. LAI can be estimated using different techniques such as destructive sampling, vegetation indices and optical instruments. This paper investigates LAI measurements in white beans and corn canopies using two optical instruments, the LI-COR LAI-2000 and the Tracing Radiation and Architecture of Canopies (TRAC), a prototype instrument designed by the Canada Centre for Remote Sensing (CCRS). LAI estimates provided by each instrument are compared and analysed. Also, further investigation is done in regards to the percent crop cover data and LAI values from the LAI-2000 and the TRAC. Preliminary results indicate that LAI measurements with the LAI-2000 and the TRAC do not correlate very well. It was also found that LAI-2000's LAI estimates correlate better with the percent crop cover than the TRAC. Accordingly, the LAI-2000 provides LAI values that are more accurate than those provided with the TRAC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".