Natural Titanite Reference Materials for<i>In Situ</i>U‐Pb and Sm‐Nd Isotopic Measurements by<scp>LA</scp>‐(<scp>MC</scp>)‐<scp>ICP</scp>‐<scp>MS</scp>
Bibliographic record
Abstract
Titanite is a common accessory mineral that preferentially incorporates considerable amounts of U and light rare earth elements in its structure, making it a versatile mineral forin situU‐Pb dating and Sm‐Nd isotopic measurement. Here, we presentin situU‐Pb ages and Sm‐Nd isotope measurement results for four well‐known titanite reference materials (Khan,BLR‐1,OLT1 andMKED1) and eight titanite crystals that could be considered potential reference material candidates (Ontario,YQ‐82, T3, T4,TLS‐36,NW‐IOA, Pakistan and C253), with ages ranging from ~ 20 Ma to ~ 1840 Ma. Results indicate thatBLR‐1,OLT1, Ontario,MKED1 and T3 titanite have relatively homogeneous Sm‐Nd isotopes and low common Pb and thus can serve as primary reference materials for U‐Pb and Sm‐Nd microanalysis.YQ‐82 and T4 titanite can be used as secondary reference materials forin situU‐Pb analysis because of their low common Pb. However, internal structures and mineral inclusions inYQ‐82 will require careful selection of suitable target domains. Pakistan titanite is almost concordant with an age of 21 Ma and can be used as a reference material when dating Cenozoic titanite samples.
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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 | 0.001 | 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) | 0.004 | 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".