Best Practices for Reporting Atom Probe Analysis of Geological Materials
Bibliographic record
Abstract
The application of atom probe tomography (APT) within the Earth and planetary sciences has produced novel data sets that answer fundamental questions about the near-atomic scale distribution of elements and isotopes within minerals. It involves the incremental evaporation, detection, and subsequent computer reconstruction of charged particles from a needle-shaped specimen. The range of applications is growing such that protocols for reporting are needed for APT data comparison and quality assessment among natural materials. A particular challenge of APT science relates to documenting the instrumental and analyst-dependent conditions that affect the mass spectral and spatial qualities of the data and their interpretation. This contribution outlines recommended data reporting procedures for publication of ATP data in terms of the sample preparation, data collection, and reconstruction phases as well as the characterization and interpretation of the reconstructed volume. Coordinated reporting of this basic information will promote efficient communication of protocols, and aid in the evaluation of published atom probe data as geologists continue to explore atomic compositions and distributions at nanoscale.
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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 | 0.128 | 0.268 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.010 | 0.009 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.037 | 0.078 |
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".