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Record W4400493286 · doi:10.1007/1345_2024_253

Optimizing Airborne Flight Line Spacing for Geoid Determination with Full Gravity Vectors

2024· book-chapter· en· W4400493286 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Association of Geodesy symposia · 2024
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsYork UniversityGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsGeoidGeodesyAerospace engineeringLine (geometry)Remote sensingGeologyEnvironmental sciencePhysicsMeteorologyGeophysicsMathematicsGeometryEngineering

Abstract

fetched live from OpenAlex

Abstract The horizontal components of the airborne gravity vector are equivalent to the deflection of the vertical at the flight level and contain signals of the slope of Earth’s gravity field. We test the contribution of such components in finding the optimum flight line spacing for geoid modelling. We use the one-step integration method and create a system of linear equations containing the three components of the airborne gravity vector as observations and solve the geodetic boundary value problem on the reference ellipsoid as an overdetermined weighted least-squares problem. We test our methodology in the Colorado region in the USA given that it is one of the most challenging areas for geoid modelling. We show that by incorporating the horizontal components at the flight level, one can increase the flight line spacing by almost 40%, thereby significantly reducing the cost of airborne surveys while maintaining the same accuracy in the estimated geoid heights as when the scalar value of gravity is used.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.219
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it