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Record W2153829716 · doi:10.1109/hpcs.2005.29

Grid-Enabling the Global Geodynamics Project: The Introduction of an XML-Based Data Model

2005· article· en· W2153829716 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsYork University
Fundersnot available
KeywordsMetadataComputer scienceXMLGeodynamicsData scienceMarkup languageFocus (optics)GridXQueryWorld Wide WebXML databaseGeography

Abstract

fetched live from OpenAlex

The Global Geodynamics Project (GGP) provides a reasonable representation of the scientific collaboration evident in small-to-medium-scale initiatives. GGP also provides data management challenges that are different from those typically expressed by other areas of the physical sciences - e.g., high energy physics. These distinctions make GGP an interesting candidate for assessing the challenges and opportunities associated with technically enabling collaborative science via grid computing. Emphasis is placed here on the introduction of an XML-based data model into the GGP. Although it is concluded that Earth Sciences Markup Language (ESML) is highly effective and efficient in introducing a new data model, and paves the way for structural transformations on data, challenges and opportunities are also identified. Metadata (data about data) provides the gravest concern and therefore the most-important focus for further research.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.563

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.000
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 head0.043
GPT teacher head0.300
Teacher spread0.257 · 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