Comparison of lithium borate fusion and four-acid digestions for the determination of whole-rock chemistry – implications for lithogeochemistry and mineral exploration
Bibliographic record
Abstract
Mining and exploration companies routinely use four-acid digestion (4AD), inductively coupled plasma, atomic emission spectra/mass spectrometry methods from commercial assay laboratories for analysing drill and rock samples for lithogeochemical assessment and resource reporting. This method is also known to exhibit lower recovery of elements hosted by resistate minerals. To assess the impact of lower recoveries on lithogeochemical interpretation, a suite of commonly used elements for lithogeochemical analysis (high-field-strength elements Zr, Hf, Nb, Ta, Ti and Eu and transition elements V and Sc) was analysed by 4AD and alkali fusion/acid digestion (AFAD). Lower recoveries in the 4AD relative to the AFAD were recorded for Zr, Hf, Nb, Ta, Ti and Eu; Sc and V reported similar concentrations for both decomposition methods. Despite the lower recoveries for Nb, Ta and Ti, element ratios were largely preserved with the 4AD method due to the recoveries covarying at a 1:1 ratio. A plot of Ti/Nb against V/Sc was found to be largely unaffected by decomposition method, producing similar compositional classifications between the two digestion methods. Use of the Eu anomaly (Eu/Eu*) to determine plagioclase fractionation was also found to be unaffected by decomposition method. In contrast, a standard Zr/Ti v. Nb/Y discrimination plot produced incorrect classifications with 4AD producing more mafic and alkaline classifications relative to the AFAD method. Magmatic fertility interpretations utilizing Zr/Hf were also found to be affected in the 4AD results due to the lower recovery of Zr relative to Hf. This resulted in a bias in the 4AD results and produced false-positive anomalism in fertility assessments. Multiple decomposition methods including combinations of acid and fusion methods are recommended for lithogeochemical analysis utilizing large regions of the periodic table. However, if only 4AD data are available, plots such as Ti/Nb v. V/Sc and Nb/Ta, which preserve their ratios, can be used for lithogeochemical classification. Supplementary material: Wholerock geochemical data and detailed methods are available at https://doi.org/10.6084/m9.figshare.c.6444444
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".