PORTABLE X-RAY FLUORESCENCE TRACE METAL MEASUREMENT IN ORGANIC RICH SOILS: PXRF RESPONSE AS A FUNCTION OF ORGANIC MATTER FRACTION
Bibliographic record
Abstract
Abstract The influence of organic matter fraction on portable X-Ray fluorescence (pXRF) trace metal measurements was investigated through the incremental addition of three organic matter surrogates (cellulose, graphite powder, and confectioner's sugar) to a soil matrix. Each surrogate was independently added to and homogenized with samples of Natural Resources Canada Till-1 standard reference material that was initially expunged of organic matter through combustion. Incremental addition was performed 20 times for each surrogate, and concentrations of thirteen elements were measured as a function of varying organic matter fractions using a Thermo Scientific Niton XL3t GOLDD+ 950 XRF analyzer. Results demonstrate attenuation of the pXRF signal with increasing sample organic matter fraction; however, elementally dependent deviations from expected concentrations were also observed. An empirical organic matter fraction-dependent calibration method was developed and its performance was evaluated using four unmodified soil standards with known organic matter content. Estimates incorporating soil organic matter differed from conventional calibration estimates neglecting organic matter content, yet were able to reproduce standard reference material values with similar success.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".