Replication Data for: Origin of the analytical 183W effect and its implications for tungsten isotope analyses.
Bibliographic record
Abstract
Mass-independent tungsten isotope variations provide critical insights into the timing and nature of processes that occurred in the early Solar System and during planetary differentiation. However, W isotope analyses are often compromised by an analytical artifact manifesting itself as an apparent deficit in 183W, whose origin and nature have remained enigmatic. Here, by evaluating previously published high-precision W isotope data for a large and diverse set of terrestrial samples, we demonstrate that this artifact occurs independent of the type of mass spectrometer and confirm that it can be attributed to mass-independent fractionation of 183W. Contrary to previous proposals, we find that this ‘analytical183W effect’ cannot be explained by a nuclear field shift, but may instead reflect a magnetic isotope effect. Regardless of its exact origin, our investigation reveals that this artifact is induced during the chemical separation of W, and that the specific combination of chromatographic purification and dry-down procedure determines its overall magnitude. Within a given analytical protocol, however, its size is strongly controlled by the amount of W that is processed, where the 183W effect increases with decreasing amount of W. Therefore, this work resolves apparent inconsistencies between previous studies regarding the occurrence and magnitude of the 183W effect, and provides directions for its mitigation and reliable correction. This in turn is crucial for the accurate interpretation of W isotope data with respect to radiogenic and nucleosynthetic anomalies for both terrestrial and meteoritic materials.
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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 | 0.013 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.290 | 0.193 |
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".