LA‐(MC)‐ICP‐MS Trends in 2006 and 2007 with Particular Emphasis on Measurement Uncertainties
Bibliographic record
Abstract
Research in 2006 and 2007 dealing with laser ablation‐(multicollector)‐inductively coupled plasma‐mass spectrometry, LA‐(MC)‐ICP‐MS, involved studies concerned with optimising the technique itself, as well as applying the method to a variety of problems in the Earth sciences. The causes of elemental and isotopic fractionation produced during laser ablation continues to be of considerable interest, with evidence mounting that processes occurring both at the ablation site and in the argon plasma of the ICP are culpable. There is growing excitement in the use of femtosecond lasers for LA‐(MC)‐ICP‐MS, with the hope that they reduce or eliminate melting and non‐congruent volatilisation at the ablation site and thus approach stoichiometric sampling. Ablation chamber design emerged as a serious concern, particularly with respect to achieving the rapid washout needed for fine‐scale compositional mapping of geological objects. LA‐MC‐ICP‐MS provided data for a wide range of isotopic systems, especially hafnium, but also B, S, Mg, Cu, Fe, Sr, Nd, Pb and U. Measurement uncertainties in LA‐ICP‐MS were discussed by several researchers, and are critically reviewed here ‐ total uncertainties for trace element concentration measurements of silicates including errors on the calibration values of common reference materials are ∼10% (95% confidence limits), though the precision of individual spot measurements (50 to 100 μm) is much better, ∼1% RSD, using a 193 nm laser and a sector field‐ICP‐MS. LA‐ICP‐MS U‐Pb ages for zircon and other U‐rich accessory phases are claimed by most geoanalysts to have 2s uncertainties of ∼0.7 and 1.3% respectively but the actual accuracy of the method is probably only as good as ∼2% (2s), when uncertainties associated with laser‐induced Pb/U fractionation are included.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".