Taking the “Boulder” Step From Static to Dynamic Geoid: 2009 Workshop on Monitoring North American Geoid Change; Boulder, Colorado, 21–23 October 2009
Bibliographic record
Abstract
As coastal communities are increasingly affected by sea level rise and flooding from extreme weather events, and as less evident (yet significant) tectonic shifts reshape the North American continent, the need for elevation data that are accurate, consistent, updated, and easily accessible has become critical. Currently, however, the vertical datums in North America are defined by tide gauge and leveling observations, which inevitably become outdated and are costly to replace or repeat. Therefore, two North American governments (Canada and United States) have resolved that the next generation of their national vertical datums will be geoid‐ based and accessible through Global Navigation Satellite System (GNSS) technology. To adequately serve as the reference surface for a future vertical datum, the geoid must be modeled accurately and its changes over time must be monitored. But what mix of tools and techniques could fulfill this requirement? To address this question and to plan for a campaign to monitor North American geoid change, experts from North America (including United States, Canada, and Mexico) and Europe specializing in satellite and terrestrial gravimetry as well as satellite positioning convened in Colorado.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".