In situ location and U‐Pb dating of small zircon grains in igneous rocks using laser ablation–inductively coupled plasma–quadrupole mass spectrometry
Bibliographic record
Abstract
A new U‐Pb zircon dating protocol for small (10–50 μ m) zircons has been developed using an automated searching method to locate zircon grains in a polished rock mount. The scanning electron microscope‐energy‐dispersive X ray spectrum‐based automated searching method can routinely find in situ zircon grains larger than 5 μ m across. A selection of these grains was ablated using a 10 μ m laser spot and analyzed in an inductively coupled plasma‐quadrupole mass spectrometer (ICP‐QMS). The technique has lower precision (∼6% uncertainty at 95% confidence on individual spot analyses) than typical laser ablation ICP‐MS (∼2%), secondary ion mass spectrometry (<1%), and isotope dilution‐thermal ionization mass spectrometry (∼0.4%) methods. However, it is accurate and has been used successfully on fine‐grained lithologies, including mafic rocks from island arcs, ocean basins, and ophiolites, which have traditionally been considered devoid of dateable zircons. This technique is particularly well suited for medium‐ to fine‐grained mafic volcanic rocks where zircon separation is challenging and can also be used to date rocks where only small amounts of sample are available (clasts, xenoliths, dredge rocks). The most significant problem with dating small in situ zircon grains is Pb loss. In our study, many of the small zircons analyzed have high U contents, and the isotopic compositions of these grains are consistent with Pb loss resulting from internal α radiation damage. This problem is not significant in very young rocks and can be minimized in older rocks by avoiding high‐U zircon grains.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".