Preliminary comparison results of four different types of disdrometer in the DEVEX experiment
Bibliographic record
Abstract
The DEVEX experiment (Disdrometer EValuation EXperiment) was conducted in \nthe spring and summer of 2002 by institutions from the U.S., Canada, and France \nto compare measurements of rain drop size distributions measured with different \ntypes of disdrometers. The instruments were located closely to each other so as to \nprovide information on the same rain events. The experiment took place at the Iowa \nCity Municipal Airport, in Iowa City, IA. Other instruments at the site were a tipping \nbucket rain gauge, a vertically pointing X-band radar, an anemometer, and a wind \nprofiler. \nDetermining the size distribution of rain drops is important in many fields such \nas remote sensing of precipitation, radio wave propagation through rain as well as \nground-based weather radars. The present work describes the first results obtained \nby comparing instruments based on different measurement principles. Rain gauges, \nwhich are simple instruments, only give an integrated estimate of rain. However, \nthis estimate is very accurate and was used in the experiment as a reference for the \ncomparison between disdrometers. \nThe results presented here show that the various instruments may give strongly \ndeviating results according to the rain rate range of interest. \nThe objective of this work was to show the advantages and drawbacks of each \nof these measurement principles in the various types of rain events encountered \nduring the DEVEX experiment.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".