An analytical protocol for determining the elemental chemistry of Quaternary sediments using a portable X-ray fluorescence spectrometer
Bibliographic record
Abstract
Advances in portable X-ray fluorescence (pXRF) technology have resulted in the ability to collect high-quality geochemical data for sediments at a fraction of the cost of traditional laboratory methods. The analytical quality of pXRF derived geochemical data is dependent on numerous factors including sample heterogeneity, grain size, moisture content, sample thickness, and instrument specifications such as power parameters, X-ray tube type, and dwell time. In order to ensure precise and accurate results using a pXRF spectrometer an analytical protocol has been developed using reference materials and prepared Quaternary sediments. This protocol considers 1) Sample preparation, 2) Analysis, and 3) Data compilation/presentation. Although the pXRF spectrometer provides concentrations for 41 elements it has been determined that only a subset of these elements meet the criteria for near definitive, quantitative, and qualitative data. Although the analytical protocol is robust, sample collection and preparation is still the key to a successful geochemical study. A significant advantage of pXRF technology is the opportunity to refine sampling strategies in near real time and the ability to add additional samples to a project with little budget increase.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.014 |
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".