The daughter–parent plot: a tool for analyzing thermochronological data
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Bibliographic record
Abstract
Abstract. Data plots of daughter against parent concentration (D–P plots) are a potential tool for analyzing low-temperature thermochronology, similar to isochron plots in radioisotopic geochronology. Their purposes are to visualize the main term of the radiometric age equation – the daughter–parent ratio – and to inspect the daughter–parent relationship for anomalies indicating influences of geological processes or analytical bias. The main advantages of the D–P plot over other data analysis tools are (1) its ability to detect systematic offsets in D and P concentrations, (2) its unambiguous representation of radiation-damage-dependent daughter retention, and (3) the possibility to analyze potential age outliers. Despite these benefits, the D–P plot is currently not used for analyzing low-temperature thermochronology data, e.g., from fission-track, (U–Th) / He, or zircon Raman dating. We present a simple, decision-tree-based classification for daughter–parent relationships based on the D–P plot that places a dataset into one of seven classes: linear relationship with zero intercept, cluster, linear relationship with systematic offset, nonlinear relationship, several age populations, scattered data, and inverse relationship. Assigning a class to a dataset enables choosing further data analysis steps and how to report a sample age, e.g., as a pooled, central, or isochron age or a range of ages. This classification scheme aims at facilitating thermochronological data analysis and making decisions more transparent. We demonstrate the proposed procedure by analyzing published datasets from a variety of geological settings and thermochronometers and introduce Incaplot, which is graphical user interface software that we developed to facilitate D–P plotting of thermochronology data.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it