Errors of Naturally Ventilated Air Temperature Measurements in a Spatial Observation Network
Bibliographic record
Abstract
Abstract A spatial network of 25 air temperature sensors was deployed over an area of 3.5 km × 3.5 km of agricultural land, aiming to calculate the sensible heat flux by spatial averaging instead of temporal averaging. Since temperature sensors in naturally ventilated solar radiation shields were used for these measurements, a correction for radiative heating had to be applied. In this study, the approach of Anderson and Baumgartner was adapted to the cube-shaped HOBO solar radiation shields. This semiempirical correction depends on the shield’s area normal to the sun in addition to solar radiation and wind speed. The required correction coefficients, which can be universally applied for this type of shield, were obtained through comparison with fan-aspirated temperature measurements at one site. The root-mean-square error of the HOBO temperature measurements was reduced from 0.49° to 0.15°C after applying this radiation correction.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".