Contribution to the discussion on processing and measurement methodology of apatite fission-track analysis
Bibliographic record
Abstract
Apatite fission track dating and T,t-modelling are now a well-established thermochronological instruments for investigating geological problems (Malusà and Fitzgerald, 2019). In the course of their development, complicating factors that affect the track counts and confined track lengths in geological samples were corrected for, foremost among them the crystallographic orientation of the confined track and the chemical composition of the apatite (Green et al., 1986, and subsequent papers). Methods have also been proposed to improve the confined track statistics, using 252Cf irradiation, ion irradiation, fracturing, and re-etching (Yamada et al., 1998). However, there is to date no adequate correction for the protocol used to reveal the tracks, which differs from lab to lab although all are based on nitric acid. Recent step-etch experiments with the most used etchants show that both the duration of the etch and the temperature and concentration of the solution have non-negligible effects on the measured lengths (Sobel and Seward, 2010; Jonckheere et al., 2017 and references therein; Tamer et al., 2019). Earlier attempt to overcome these problems investigated etching for such a time that the track openings conform to a pre-determined size (Ravenhurst et al., 2003) or measuring confined tracks of a given minimum width (Yamada et al., 1993). The first method has the drawback that the widths of the host tracks and confined tracks are not directly related, whereas the second fails to consider the anisotropic width of confined tracks. In our geological investigation of the German Naab area, we adopt a step-etch approach, measuring the c-axis angle, length, width and dip of each individual confined track after 20s and 30s immersion in 5.5 M HNO3. From the width increase we calculate the rate of widening of the track (apatite etch rate; Aslanian et al., 2021), and from that the effective etch time tE, i.e., the true duration that the confined track has been etched, equal to the immersion time minus the time needed for the etchant to reach the specific confined track. Our results show that the confined track lengths are correlated with their effective etch times. This information is used to account for etch-protocol-related differences between the induced and fossil track lengths entered in the T,t-modelling software. We envisage this will improve the accurateness and resolution of the resulting T,t-paths. We will check this against the excellent independent geological constraints that exist for the Naab region. The research was funded by the EU/MEYS (CZ.02.2.69/0.0/0.0/19_074/0014756). References Aslanian et al., 2021. American Mineralogist. In press. Green et al., 1986. Chemical Geology 59, 237-253. Jonckheere et al., 2017. American Mineralogist 102, 987-996. Malusà and Fitzgerald, 2019. Fission-Track Thermochronology and its Application to Geology. Pp 393. Ravenhurst et al., 2003. Canadian Journal of Earth Sciences 40, 995-1007. Sobel and Seward, 2010. Chemical Geology 271, 59-69. Tamer et al., 2019. American Mineralogist 104(10), 1421-1435. Yamada et al., 1993. Chemical Geology 122, 249-258 Yamada et al., 1998. Chemical Geology 149, 99–107.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.020 |
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".