Bibliographic record
Abstract
Abstract. The highest precision and accuracy in U–Pb geochronology is achieved using isotope dilution thermal ionisation mass spectrometry (ID-TIMS), a technique which owes its reliability to precise Pb and U isotope ratio analysis, a largely unified framework of lab protocols, and common isotopic tracers with accurately determined compositions. However, while hardware and protocol developments have steadily improved the analytical precision, the level to which ID-TIMS U–Pb dates from different laboratories agree remains largely unquantified. To better assess both internal repeatability and interlaboratory reproducibility of this method, we have conducted an experiment in which a large batch of natural zircon was dissolved, mixed with a newly prepared 205Pb–233U–235U tracer, and distributed as solution to participating laboratories. Thus prepared, pre-spiked, homogeneous PLES535 solution underwent the full sample preparation and analysis process separately in each lab, allowing a maximally unbiased comparison of the entire analytical procedure on a sample of unknown age. The results from 14 instruments at 11 institutions demonstrate internal repeatability of individual labs at 5 to 10 U–Pb analyses, with MSWD values generally indicative of single age populations. Lab weighted-mean 206Pb/238U and 207Pb/235U ages for the 337 Ma zircon solution agree within 0.05 % and 0.09 % (two standard deviations), respectively. This underscores the reliability of the participating laboratories for precise and accurate zircon U–Pb analyses, while highlighting the need for continued exchange on lab protocols and method improvement. We identify likely reasons for the remaining interlaboratory bias and discuss ways forward toward the goal of 0.01 % reproducibility.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.030 | 0.017 |
| Insufficient payload (model declined to judge) | 0.151 | 0.129 |
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".