Extending the concept of background to soil gas: natural radon concentrations in soils of Campania region.
Bibliographic record
Abstract
<p>Radon is an ubiquitous radioactive gas proceeding from the decay of some radionuclides, mostly abundant in igneous rock and volcanic soils; it is the main source of natural radiation to which human beings are exposed during their life. Campania, a region located on the south-western sector of the Italian peninsula, has a territory mostly characterized by the presence of volcanic lithotypes and sediments. <br>An empirical method was applied to determine the concentration of Rn-222 in soils of Campania region by using radiometric  and compositional data recorded in two extensive different environmental prospecting campaigns completed in 2003 and 2015, respectively.</p><p>Radiometric surveys were carried out with a nominal density of 1 station per 5 sqkm with a GRS-500 portable scintillometer produced by Scintrex Ltd (Ontario, Canada); topsoil samples were collected at 3535 sites regularly spread across the whole regional area with a nominal density of 1 sample per sqkm. Samples destinated to chemical analyses were analysed by ICP-MS after an aqua regia digestion at the ACME Analytical Laboratories Ltd (now Bureau Veritas) in Vancouver, Canada.  </p><p>Specifically, the concentrations of  U, Th and K  in topsoil samples  and the activity (gamma radiation) generated by the decay of U-238, Th-232 and K-40 (expressed as Bq) at  each measurement station were used as proxies in order to determine the variation of Rn-222 flux from the ground and to estimate the distribution pattern of geogenic radon potential (GPR) across the region.</p><p>The use of a sequence of specific equations led to estimate the terrestrial gamma dose rate (nSv/h) at 1 m above the ground surface starting from both datasets and, therefore, allowed the generation of the Rn-222 flux and GPR maps for the whole regional territory.</p><p>Both Radon flux and GPR raster maps were produced by mean of some specific geospatial elaborations and the estimated values were compared among them and validated trough the completion of some field measurements.</p>
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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".