U‐Pb Detrital Zircon Analysis – Results of an Inter‐laboratory Comparison
Bibliographic record
Abstract
Inter‐laboratory comparison of laser ablationICP‐MSandSIMSU‐Pb dating of synthetic detrital zircon samples provides an insight into the state‐of‐the art of sedimentary provenance studies. Here, we report results obtained from ten laboratories that routinely perform this type of work. The achieved level of bias was mostly within ± 2% relative to theID‐TIMSU‐Pb ages of zircons in the detrital sample, and the variation is likely to be attributed to variable Pb/U elemental fractionation due to zircon matrix differences between the samples and the reference materials used for standardisation. It has been determined that ~ 5% age difference between adjacent age peaks is currently at the limit of what can be routinely resolved by thein situdating of detrital zircon samples. Precision of individual zircon age determination mostly reflects the data reduction and procedures of measurement uncertainty propagation, and it is largely independent of the instrumentation, analytical technique and reference samples used for standardisation. All laboratories showed a bias towards selection of larger zircon grains for analysis. The experiment confirms the previously published estimates of the minimum number of grains that have to be analysed in order to detect minor zircon age populations in detrital samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".