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Record W4402261046 · doi:10.62973/12-093

OWS-9: UML-to-GML-Application-Schema (UGAS) Conversion Engineering Report

2013· report· en· W4402261046 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsnot available
FundersDefence Science and Technology GroupNatural Resources CanadaU.S. Army Corps of EngineersDefence Science and Technology LaboratoryNational Geospatial-Intelligence AgencyFederal Aviation AdministrationU.S. Geological SurveyNational Aeronautics and Space Administration
KeywordsSchema (genetic algorithms)Unified Modeling LanguageComputer scienceProgramming languageDatabaseSoftware engineeringInformation retrievalSoftware

Abstract

fetched live from OpenAlex

The main scope of the schema automation activities in the OWS-9 initiative was twofold: Support for the SWE Common 2.0 XML Schema encoding rule Development of and support for an encoding rule for JSON instance data In both cases the scope includes implementation of the encoding rules in ShapeChange.In addition, an initial analysis of the possibilities for generating SWE Common 2.0 record descriptions from schemas in UML has been conducted and the results are described in this document.The approach and results to both work items are described and discussed in this engineering report.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.256
Teacher spread0.241 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2013
Admission routes1
Has abstractyes

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