<tt>PbIso</tt>: an R package and web app for calculating and plotting Pb isotope data
Bibliographic record
Abstract
The package PbIso is a free and open R toolbox for commonly used calculations and plots of Pb–Pb isotope data and for generating Pb evolution models. In this paper, we review Pb isotope systematics and the calculations that are commonly used, such as model age, model source μ (238U/204Pb), time-integrated κ (232Th/238U), and initial Pb isotope ratios. These equations are implemented into R functions in the package PbIso. In addition, functions are provided for generating Pb evolution models, paleoisochrons, and isochrons. This allows users to apply calculations to their data in a straightforward way while providing transparency and flexibility of the calculations used. We have implemented some basic features of the PbIso package into an online shiny R application (see https://shereearmistead.github.io/software/pbiso ), which makes it easy for users without any R experience to use these calculations with their own data and to generate plots. We have provided a case study from the Superior Province in Canada, showing how different Pb evolution models can be generated in PbIso and compared to Pb isotope data.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.143 | 0.142 |
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".