Preliminary retrievals of deformation rates based on 2017-2023 Sentinel-1 data computed with the MSBAS system.
Bibliographic record
Abstract
Supplementary information for the manuscript Deformation rates for North America and Eurasia from Sentinel-1 DInSAR: processing methodology with examples Preliminary retrievals of deformation rates during 2017-2023 computed from Sentinel-1 data with the MSBAS system Part I: Canada (Ascending) Part II: Canada (Descending) Part III: China (Ascending) Part IV: China (Descending) Part V: Russia (Ascending) Part VI: Russia (Descending) Part VII: Central Asia and the Caucasus Part VIII: Glaciers (from speckle offsets), Canada Part IX: Glaciers (from speckle offsets), Russia For additional information contact Sergey Samsonov at sergey.samsonov@nrcan-rncan.gc.ca.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.014 | 0.007 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.019 |
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".