EBSD Data for garnet-amphibolites and epidote-amphibolites from Mont Albert, Québec
Bibliographic record
Abstract
Aztec Project Files and montaged large-area maps for EBSD data from garnet amphibolites and epidote-amphibolites from Mont Albert. Each sample has a folder with raw data that can be opened in Aztec. Samples KMA22-02 and KMA24-13 also include quartz vein data. For each sample, exported ctf, crc, cpr and H5OINA files for montaged large-area maps are provided; these can be opened in various processing softwares (e.g., AztecCrystal) or processed in Matlab with MTEX. No data cleanup routines have been applied to these data. The data is provided in 5 subfolders. Detailed information about the files in these subfolders as well as information on how the data is processed is given in the explanatory file Readme.txt. These data are processed, presented, and interpreted in the following article: Kotowski, A. J., Seyler, C. E., Kirkpatrick, J., & van Hinsbergen, D. J. (2025). Coupled Mineral-Mechanical Changes During Plate Interface Cooling May Explain Catastrophic Subduction Initiation. Authorea Preprints. Under review in Journal of Geophysical Research: Solid Earth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.023 |
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".