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Record W6963325093 · doi:10.18738/t8/ze7dud

CSR GRACE and GRACE-FO Ocean Mascons RL06.2EQ

2024· dataset· en· W6963325093 on OpenAlexaboutno aff

Bibliographic record

VenueTexas Digital Library (University of Texas) · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAnomaly (physics)GridQuarter (Canadian coin)Sampling (signal processing)Natural disasterGlobal Positioning SystemCorporate social responsibility

Abstract

fetched live from OpenAlex

Monthly mass anomaly grids from GRACE and GRACE-FO determined from CSR RL06.2 processing with specific handling of the major earthquakes in Japan and Andaman Bay. The RL06.2EQ mascons are directly comparable to the CSR RL06.2 official mascon product. The earthquake model is provided as a companion correction grid. Users interested in the mass anomaly signal, free of the contributions from the earthquake co-seismic and post-seismic signals, will substract the earthquake model grid from the RL06.2EQ mascon grid. The grids are provided globally with a quarter degree sampling in longitude/latitude. Only the ocean mascons are reported. The land mascons are set to "NaN". The grids cover the GRACE and GRACE-FO period from 04/2002 to 02/2023.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.063
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.007
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0630.083

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 head0.011
GPT teacher head0.193
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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