Correction to the plant canopy gap-size analysis theory used by the Tracing Radiation and Architecture of Canopies instrument
Bibliographic record
Abstract
A plant canopy gap-size analyzer, the Tracing Radiation and Architecture of Canopies (TRAC), developed by Chen and Cihlar [Appl Opt. 34, 6211(1995)] and commercialized and by 3rd Wave Engineering (Nepean, Canada), has been used around the world to quantify the fraction of photosynthetically activeradiation absorbed by plant canopies, the leaf area index (LAI), and canopy architectural parameters. The TRAC is walked under a canopy along transects to measure sunflecks that are converted into a gap-size distribution. A numerical gap-removal technique is performed to remove gaps that are not theoretically possible in a random canopy. The resulting reduced gap-size distribution is used to quantify the heterogeneity of the canopy and to improve LAI measurements. It is explicitly shown here that the original derivation of the clumping index was missing a normalization factor. For a very clumped canopy with a large gap faction, the resulting LAI can be more than 100% smaller than previously estimated. A test case is used to demonstrate that the new clumping index derivation allows a more accurate change of LAI to be measured.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".