CHAMP Gravity Results Using the Energy Integral Ap- proach with Emphasis on Algorithmic Aspects
Bibliographic record
Abstract
The poster stresses two main aspects of the processing of CHAMP GPSand accelerometer data. 1. Kinematically derived orbit determination yields position only. Velocities have to be derived numerically. 2. In the further processing accelerometer data is used to correct for dissipative forces. The necessary calibration is done using crossover points. Preliminary results are on the dm-level. Introduction: • Feasibility of the energy integral approach is proven. • The basic characteristic is the use of GPS derived position and velocity data and the correction for nongravitational forces derived from accelerometer data. • Purely kinematic CHAMP orbits avoid the contamination with a priori gravity field information but velocities have to be derived numerically. • In the data processing a calibration of the accelerometer data is necessary to account for the bias and scale of the accelerometer. Acknowledgements: • Geoforschungszentrum (GFZ) Potsdam, Germany • Institute for Astronomical and Physical Geodesy (IAPG), TU Munich, Germany • Institute for Theoretical Geodesy (ITG), University of Bonn, Germany • GEOIDE Network of Centers of Excellence, Canada • NSERC, Canada • Werner Graupe International Fellowship in Engineering, U. of Calgary, Canada Conclusion: • Velocity determination is promising but problems with edge effects cause large errors • Filter technique enables smoothing of data • Results with simulated data reach level • Results with actual data indicate level • Crossover calibration necessary for drift correction • Linear Regression as adjustment model for bias and drift correction • Extension of the adjustment model for the determination of the scale of the accelerometer necessary. • Connection of daily solutions using crossover points • Time consuming crossover search • Preliminary results are on the dm-level. Geomatics Engineering, University of Calgary 2500 University Drive N.W. Calgary, AB, Canada Researchers: CHAMP Gravity Results using the Energy Balance Approach with Emphasis on Algorithmic Aspects Matthias Weigelt, mlbweige@ucalgary.ca Nico Sneeuw Crossover Calibration: • Ignoring dissipative forces the disturbing potential drifts away from a constant level (blue curve), i. e. energy dissipation takes place. • Correcting for the dissipation with raw accelerometer data yields a worse drift (red curve) due to the scale and bias of the accelerometer. • Crossover adjustment is used for calibration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".