Inter-comparison study of atmospheric <sup>222</sup> Rn and <sup>222</sup> Rn progeny monitors
Bibliographic record
Abstract
Abstract. The use of the noble gas radon (222Rn) as tracer for different research studies, for example observation-based estimation of greenhouse gas (GHG) fluxes, has led to the need of high-quality 222Rn activity concentration observations with high spatial and temporal resolution. So far a robust metrology chain for these measurements is not yet available. A 3-month inter-comparison campaign of atmospheric 222Rn and 222Rn progeny monitors based on different measurement techniques was realized during the fall and winter of 2016-2017 to evaluate: i) calibration and correction factors between monitors necessary to harmonize the atmospheric radon observations; and ii) the dependence of each monitor’s response in relation to the sampling height, meteorological and atmospheric aerosol conditions. Results of this study have shown that: i) all monitors were able to reproduce the atmospheric radon variability on daily basis; ii) linear regression fits between the monitors exhibited slopes between 0.62 and 1.17 and offsets ranging between −0.85 Bq m−3 and −0.23 Bq m−3 when sampling 2 m above ground level (a.g.l.). Corresponding results at 100 m a.g.l. exhibited slopes of 0.94 and 1.03 with offsets of −0.13 Bq m−3 and 0.01 Bq m−3, respectively; iii) no influence of atmospheric temperature and relative humidity on monitor responses was observed for unsaturated conditions; and iv) changes of the ratio between radon progeny and radon monitor responses were observed under very high atmospheric humidity and under very low atmospheric aerosol concentrations. However, a more statistically robust evaluation of these last influences based on a longer dataset should be conducted to improve the harmonization of the data.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".