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Record W4312156228 · doi:10.1029/2022jb024991

Constraints on Secular Geocenter Velocity From Absolute Gravity Observations in Central North America: Implications for Global Melting Rates

2022· article· en· W4312156228 on OpenAlexaff
A. Lambert, Jianliang Huang, Nicholas Courtier, G Pavlic

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsGeodesyPost-glacial reboundSecular variationClimatologyGlobal Positioning SystemGeologySeries (stratigraphy)Glacial periodGeophysicsGeomorphology

Abstract

fetched live from OpenAlex

Abstract Long series of absolute gravity observations at multiple sites provide a direct method of measuring the velocity of the geocenter caused by surface mass transport related to climate change. Annual absolute gravity observations and available GPS vertical data at eight sites in central North America from 1995 to 2010 are used to solve for geocenter velocity while correcting for glacial isostatic adjustment. The precision of the secular gravity trends and GPS heights at our sites, used to estimate geocenter motion, was improved by correcting for local and global water storage attraction and loading. Corrections for the loading and attraction effects of regional ice‐mass loss, the atmosphere and non‐tidal ocean were found to be minimal. Our results provide a direct measurement of the change in geocenter velocity over the time‐interval 2002–2010 compared to the time‐interval 1995–2003 of 0.68 ± 0.28 mm/yr away from North America. This suggests similar velocities in the negative Z (0°N) and positive Y (90°E) directions to those found by other studies.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.092
GPT teacher head0.338
Teacher spread0.246 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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