Raman Spectroscopy and Scanning Electron Microscopy Characterizations of Fission Track Method Datable Zircon Grains
Bibliographic record
Abstract
Spectroscopic and morphological studies, designed to improve our understanding of the physicochemical phenomena that occur during zircon crystallization, are presented. The zircon fission track method (ZFTM) is used routinely in various laboratories around the world; however, there are some methodological difficulties needing attention. Depending on the surface fission track density observed under an optical microscope, the zircon grain surfaces are classified as homogeneous, heterogeneous, hybrid, or anomalous. In this study, zircon grain surfaces are characterized using complementary techniques such as optical microscopy (OM), micro-Raman spectroscopy, and scanning electron microscopy (SEM), both before and after chemical etching. Our results suggest that anomalous grains have subfamilies and that etching anisotropy related to heterogeneous grains is due to different crystallographic faces within the same polished surface that cannot be observed under an optical microscope. The improved methodology was used to determine the zircon fission track ages of samples collected from the Bauru Group located in the north of Paraná Basin, Brazil. A total of 514 zircon grains were analyzed, consisting of 10% homogeneous, about 10% heterogeneous, about 20% hybrid, and 60% anomalous grains. These results show that the age distributions obtained for homogeneous, heterogeneous, and hybrid grains are both statistically and geologically compatible.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".