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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 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

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.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.053
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0010.008
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.057

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