Absolute gravity and GPS vertical data (1995-2010): Supporting data for Lambert et al. Constraints on secular geocenter velocity from absolute gravity observations in central North America: Implications for global melting rates
Bibliographic record
Abstract
The data set consists of an Excel file containing the supporting data for the following publication: Lambert, A., Huang, J., Courtier, N., & Pavlic, G. (2020). Constraints on secular geocenter velocity from absolute gravity observations in central North America: Implications for global melting rates<i>. J. Geophys. Res</i>., in prep.<br> The Excel data file comprises four sheets: Sheet 1: Annual absolute gravity observations at six sites (1995-2010) and two sites (2002-2010) showing site names, observation time in decimal years, gravity values and standard errors in microGal (1 microGal = 10 nm/s<sup>2</sup>), site reference gravity values, instruments used, observers names and site co-ordinates. Sheet 2: Daily GPS heights at five sites (1996/7-2010) and one site (2003-2010) showing site names, observation time in decimal years, heights and standard deviations in meters, and site co-ordinates. Sheet 3: Daily GPS heights at ten sites (2002-2010) used with data from two sites in sheet 2 to calculate vertical velocities at two absolute gravity sites (sheet 4) where no continuous GPS was available. Site co-ordinates are given in sheet 4. Sheet 4: Long-term height trends (vertical velocities) are estimated for the two sites lacking continuous GPS by using a 2-D adaptive Gaussian interpolation function, with a half-width defined as the distance to the nearest GPS site. <br>The absolute gravity drop data were processed using the Micro-g LaCoste "g8" software. The GPS data were processed with the NRCan Precise Point Positioning PPP 1.05 software (Héroux and Kouba, 2001). For each site, daily positions were computed using ionosphere-free combinations of un-differenced pseudo-range and phase observations, with satellite orbits and clocks fixed to the International GNSS Service (IGS) precise products, absolute phase-center calibrations for the GPS and satellite antennas (Schmid et al<i>.</i>, 2007), gridded Vienna Mapping Functions (VMF1, Boehm et al.<i>, </i>2006) for the troposphere model, and solid earth and ocean tide corrections. The GPS post-processing was originally carried out in support of Mazzotti et al. (2011).<b>References:</b> Boehm, J., Werl, B., & Schuh, H. (2006). Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Median-Range Weather Forecast operational analysis data. <i>J. Geophys. Res.</i>, 111, B02406. https://doi.org/10.1029/2005JB003629 Héroux, P., & Kouba, J. (2001). GPS Precise Point Positioning using IGS orbit products. <i>Phys. Chem. Earth (A)</i>, 26, 573-578. https://doi.org/10.1016/S1464-1895(01)00103-X Mazzotti, S., Lambert, A., Henton, J., James, T.S., & Courtier, N. (2011). Absolute gravity calibration of GPS velocities and glacial isostatic adjustment in mid-continent North America. <i>Geophys. Res. Lett., 38</i>, L24311. https://doi.org/10.1029/2011GL049846 Schmid, R., Steigenberger, P., Gendt, G., Ge, M., & Rothacher, M. (2007). Generation of a consistent absolute phase center correction model for GPS receiver and satellite antennas. <i>J. Geod.</i>, 81 (12) 781-798. https://doi.org/10.1007/s00190-007-0148-y<b>Data Sources and Open Data Policy</b> Absolute gravity data source: Geological Survey of Canada. GPS data sources: Canadian Active Control System (CACS) data from Canadian Geodetic Survey’s Geodetic Data Products web site, NASA Crustal Dynamics Data Information System (CDDIS), and U.S. National Geodetic Survey, Continually Operating Reference Stations (CORS) data download site.<br> Use of Canadian Geodetic Survey products and data is subject to the Open Government Licence - Canada © Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources, 2020<br>
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".