COMPARISON OF RESULTS FOR QUARTER 4 SURFACE WATER SPLIT SAMPLES COLLECTED AT THE NUCLEAR FUELS SERVICES SITE, ERWIN, TN
Bibliographic record
Abstract
Oak Ridge Associated Universities (ORAU), under the Oak Ridge Institute for Science and Education (ORISE) contract, collected split surface water samples with Nuclear Fuel Services (NFS) representatives on June 12, 2013. Representatives from the U.S. Nuclear Regulatory Commission (NRC) and the Tennessee Department of Environment and Conservation were also in attendance. Samples were collected at four surface water stations, as required in the approved Request for Technical Assistance number 11-018. These stations included Nolichucky River upstream (NRU), Nolichucky River downstream (NRD), Martin Creek upstream (MCU), and Martin Creek downstream (MCD). Both ORAU and NFS performed gross alpha and gross beta analyses, and Table 1 presents the comparison of results using the duplicate error ratio (DER), also known as the normalized absolute difference. A DER ≤ 3 indicates at a 99% confidence interval that split sample results do not differ significantly when compared to their respective one standard deviation (sigma) uncertainty (ANSI N42.22). The NFS split sample report specifies 95% confidence level of reported uncertainties (NFS 2013). Therefore, standard two sigma reporting values were divided by 1.96. In conclusion, most DER values were less than 3 and results are consistent with low (e.g., background) concentrations. The gross beta result for sample 5198W0014 was the exception. The ORAU gross beta result of 6.30 ± 0.65 pCi/L from location NRD is well above NFS's non-detected result of 1.56 ± 0.59 pCi/L. NFS's data package includes no detected result for any radionuclide at location NRD. At NRC's request, ORAU performed gamma spectroscopic analysis of sample 5198W0014 to identify analytes contributing to the relatively elevated gross beta results. This analysis identified detected amounts of naturally-occurring constituents, most notably Ac-228 from the thorium decay series, and does not suggest the presence of site-related contamination.
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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) | 0.001 | 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) | 0.013 | 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".