Chemostratigraphy in southern Ontario by pXRF spectrometry
Bibliographic record
Abstract
For groundwater studies, the collection of sediment geochemistry is often beyond the scope, and budget of many programs, and is generally not included as part of routine data collection. Portable x-ray fluorescence spectrometer (pXRF) has proven to be a successful tool to characterize the chemostratigraphy of glacial derived materials collected from boreholes in southern Ontario. Portable XRF provides near-total geochemistry results similar to fusion and multi-acid methods for 14 elements with minimal sample preparation and at low cost. An extensive suite of near surface samples provides characterization of the regional geochemistry. In a collaborative project with the OGS and the GSC two transects are being completed (E-W, N-S) to provide a framework of subsurface geochemistry. To eliminate the effects of variability in sample grain-size, sample volume, and to minimize nugget effects, samples are dried and sieved to <0.063 mm (silt + clay) prior to analysis. To ensure quality control, a number of Standard Reference Materials (SRM) and Certified Reference Materials (CRM) are analyzed with each project, and comparisons made with previously published results. For further quality control, a sub-suite of sediment samples are analyzed by ICP-MS/ES using lithium borate fusion, multiacid, and aqua regia digestions. Bivariate plots comparing pXRF to ICP-MS/ES display a high degree of linearity (r2 > 0.8) for Ca, Fe, K, Mn, Rb, Sr, V, Zn, Zr, and to a lesser degree for Ba, Cu, Cr, Ti, and Pb. These 14 elements return precise and generally accurate results within each borehole; however, continued analyses of CRM's and SRM's has demonstrated display drift in accuracy between projects. Resulting data for meet the US EPA criteria for quantitative data quality based on r2 values and y=mx+b relationships. Concentration levels play a significant factor in the accuracy of the pXRF data. At low concentration levels near the detection limit of the pXRF, there can be greater scatter in results. At high concentration levels, data needs to be adjusted using post-data calibration to obtain accurate results.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".