A time-of-flight resonance ionization mass spectrometer for elemental analysis of precious metals in minerals
Bibliographic record
Abstract
An instrument for time-of-flight resonance ionization mass spectrometry (TOF-RIMS) developed at the Advanced Mineral Technology Laboratory (Ontario, Canada) is described which has been applied to the quantitative trace analysis of metals in minerals. The instrument incorporates new pulsed ion optics which provide fast switching of polarity and potentials of acceleration and ion lens optics between the two consecutive laser ablation and laser photoionization steps. Pulsed mode operation allows the time-of-flight mass spectrometer to be operated at higher laser ablation powers with more efficient suppression of the primary ions which are a source of noise that degrades the ultimate sensitivity of detection. The performance of the TOF-RIMS apparatus was assessed by analyzing trace amounts of gold (Au) in sulphide, iron oxide, and silicate mineral samples. Quantification of the TOF-RIMS measurements was established on the basis of calibration curves obtained using reference samples covering three orders of magnitude in concentration. Reproducible minimum detection limits (2σ) of ⩽10 parts per billion with a precision of ∼±15% were obtained.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".