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Record W6973552303 · doi:10.57757/iugg23-3164

Towards UNB_TopoDens version 3.0: The first global 3D topographical density model

2023· article· en· W6973552303 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

VenuePublication Database GFZ (GFZ German Research Centre for Geosciences) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsGeoidFocus (optics)Geodetic datumWork (physics)Surface (topology)

Abstract

fetched live from OpenAlex

<!--!introduction!--><b></b> After the creation and publication of the UNB_TopoDens_2v01 laterally varying topographic density model, many research groups and organizations across the world implemented this high-resolution density information for a wide variety of geodetic and geophysical applications. Our most frequently asked question from users is whether there will be a three-dimensional version of the density model. The answer is yes. By combining the depth dependent estimates of density based on material bulk moduli with models of expected geological structures, we believe that the creation of a three-dimensional density model of topography is possible using already existing datasets. In this study, we investigate the depth dependent density variations within the Earth’s topography and assess the validity of using topographical surface densities to provide density estimates of various crustal structures. The goal of UNB_TopoDens 3.0 is to generate a three-dimensional density model of the Earth’s topography, which is important for geoid modelling applications. Future work will focus on refining crustal models and expanding the density model to the Mohorovičić discontinuity.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.062
GPT teacher head0.326
Teacher spread0.264 · 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