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Record W2314700021 · doi:10.1071/aseg2006ab162

GeoSciML: Enabling the Exchange of Geological Map Data

2006· article· en· W2314700021 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

VenueASEG Extended Abstracts · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsTestbedGeologic mapXMLData exchangeUnified Modeling LanguageGeological surveyComputer scienceData model (GIS)DatabaseFeature (linguistics)GeologyData miningWorld Wide WebProgramming languageGeophysicsArtificial intelligenceGeomorphologySoftware

Abstract

fetched live from OpenAlex

The CGI data model working group have established an initial geology data model and XML based exchange language to accommodate geological map data, referred to as GeoSciML. The language is based on prior work carried out at North American, European and Australian geological survey and research organisations. Unified Modelling Language (UML) has been used as a design aid for capturing the geological concepts and their properties. The UML model has then been converted to the GML-conformant GeoSciML.The design of GeoSCiML meets the short-term goal of accommodating the geoscience information presented on geological maps, as well as being fully extensible to include the full range of geological concepts covered by the geosciences. To demonstrate the ability of GeoSciML to deliver data via web feature services, a small subset has been selected as a testbed. This testbed will deliver lithostratigraphic units, boreholes, faults, contacts and compound materials from different national geological surveys.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.244
Teacher spread0.199 · 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