Towards a Global Unified Physical Height System
Bibliographic record
Abstract
The International Association of Geodesy (IAG), as the organisation responsible for advancing Geodesy, introduced in 2015 the International Height Reference System (IHRS) as the global conventional reference system for the determination of gravity field-related vertical coordinates. The definition of the IHRS is given in terms of potential parameters: the vertical coordinates are geopotential numbers (CP = W0 ‐ WP) referring to an equipotential surface of the Earth's gravity field realised by the conventional value W0 = 62 636 853.4 m2s‐2. The spatial reference of the position P for the potential WP = W(X) is given by coordinates X of the International Terrestrial Reference Frame (ITRF). At present, the main challenge is the realisation of the IHRS; i.e., the establishment of the International Height Reference Frame (IHRF): a global network with regional and national densifications, whose geopotential numbers referring to the global IHRS are known. According to the objectives of the IAG Global Geodetic Observing System (GGOS), the target accuracy of these global geopotential numbers is 3 x 10-2 m2s-2. In practice, the precise realisation of the IHRS is limited by different aspects; for instance, there are no unified standards for the determination of the potential values WP; the gravity field modelling and the estimation of the position vectors X follow different conventions; the geodetic infrastructure is not homogeneously distributed globally, etc. This may restrict the expected accuracy of 3 x 10-2 m2s-2 to some orders lower (from 10 x 10-2 m2s-2 to 100 x 10-2 m2s-2). This contribution summarises advances and present challenges in the establishment of the IHRS/IHRF.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".