Continuous GPS measurements of postglacial adjustment in Fennoscandia 1. Geodetic results
Bibliographic record
Abstract
Project BIFROST (Baseline Inferences for Fennoscandian Rebound Observations, Sea‐level, and Tectonics) combines networks of continuously operating GPS receivers in Sweden and Finland to measure ongoing crustal deformation due to glacial isostatic adjustment (GIA). We present an analysis of data collected between August 1993 and May 2000. We compare the GPS determinations of three‐dimensional crustal motion to predictions calculated using the high‐resolution Fennoscandian deglaciation model recently proposed by Lambeck et al. [1998a , 1998b] . We find that the maximum observed uplift rate (∼10 mm yr−1) and the maximum predicted uplift rate agree to better than 1 mm yr−1. The patterns of uplift also agree quite well, although significant systematic differences are evident. The root‐mean‐square residual rate for a linear error model yields estimates of rate accuracy of 0.4 mm yr−1 for east, 0.3 mm yr−1 for north, and 1.3 mm yr−1 for up; these figures incorporate model errors, however. We have also compared the values for the observed radial deformation rates to those based on sea level rates from Baltic tide gauges. The observational error for the vertical GPS rates required to give a reduced χ2 of unity is 0.8 mm yr−1. The time series do exhibit temporal variations at seasonal frequencies, as well as apparent low‐frequency noise. An empirical orthogonal function analysis indicates that the temporal variations are highly correlated among the sites. The correlation appears to be regional and falls off only slightly with distance. Some of this correlated noise is associated with snow accumulation on the antennas or, for those antennas with radomes, on the radomes. This problem has caused us to modify the radomes used several times, leading to one of our more significant sources of uncertainty.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".