Geoid investigations for the new vertical datum in Canada
Bibliographic record
Abstract
The aim of this study is to investigate the current vertical datums in North America and to assess the possible improvements to them coming from the recently obtained satellite gravity models.The study is conducted in two steps.First, the geoid models computed from the first and the second generation GOCE-only and GRACE-GOCE combined satellite-only models and truncated for different spherical harmonic degrees are compared to the GPS/leveling geoid heights which are reduced to the same spectral band of the gravity field.The GPS/leveling-derived geoid heights are used as independent controls in the assessment of the geoid models.The comparison results indicate that the GOCE models show a full power of gravity signal in terms of geoid undulation up to about spherical harmonic degree 150.Second, one of the first generation GOCE satellite-only models developed by the time-wise approach, TWO1, is complemented with local terrestrial data and tested against the GPS/leveling-derived geoid undulations in full spectrum of the gravity field and compared with the official global and regional geoid models.Based on these results there is not enough evidence indicating significant improvement (cm level) from the first generation GOCE models to the geoid modeling in Canada and the two sub-regions, the Great Lakes area and Rocky Mountains investigated, compared to EGM2008 and the existing regional geoid models.,One important contribution is the evaluation of the GOCE-only and complementary terrestrial data combined geoid model in Canada without any effect of the other satellite and geodetic techniques.The preliminary investigations on the second generation GOCE models show that the future GOCE-only and combined GRACE-GOCE models can provide more accurate and consistent geoid solutions for Canada.his professional supervision during my studies.His patience during the last few years was exceptional and much appreciated.His experience, knowledge and concerns on the topic have helped me further my studies.I would like to thank my co-supervisor Dr. Jianliang Huang from the Geodetic Survey Division of Natural Resources Canada.His continuous support and understanding during my studies are also much appreciated.He never avoided sharing his wide knowledge and ideas with me.I am greateful to Dr. Elena Rangelova for being a third "supervisor" during my studies from day to night and on weekends.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".