Aircraft‐Based Flux Sampling Strategies
Bibliographic record
Abstract
Abstract One of the essential elements of plant growth is carbon dioxide assimilation and water vapor loss. Measuring the exchange of these gases can provide an accurate picture of plant growth, health, and ultimate yield. This report describes the instrumentation used on the Canadian flux aircraft and the type of data collected for measuring gas exchange over large areas. It presents flux measurements of carbon dioxide, sensible heat (H) and latent heat (LE) using the eddy‐covariance technique. This technique provides the most direct measurements of mass and energy exchange at the land–atmosphere interface. Flux measurements obtained over wetlands near James Bay, the boreal forest in northern Saskatchewan, grasslands in Kansas, agricultural crops in California, and over the city of Fresno in California are presented as examples of the potential of this technique to characterize transfer processes over complex ecosystems. The accuracy of aircraft‐based flux measurements is examined using data obtained with other aircraft during wing‐to‐wing formation flights and with several tower‐based systems during tower fly‐by. Finally, examples of the use of these data for interpreting satellite data and for characterizing the photosynthetic response of a wide range of vegetation are presented.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".