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Record W2161086867 · doi:10.1109/hicss.2003.1174352

Storage model for CDA documents

2003· article· en· W2161086867 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
FieldDecision Sciences
TopicData Quality and Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceRelational databaseXMLInformation retrievalObject (grammar)Markup languageSemantics (computer science)DatabaseProgramming languageWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

The Health Level 7 Clinic Document Architecture (CDA) is an XML-based document markup standard that specifies the hierarchical structure and semantics of "clinical documents" for the purpose of information exchange. In this research, issues arising with the design and implementation of a DR to support efficient retrieval from CDA documents and data mining for statistical analysis purposes are explored. Both an object-relational approach and a traditional relational approach were explored and compared in terms of design, implementation issues and efficiency. Although the object-relational approach results in a simpler design, implementation is more complicated as object methods must be programmed. In the relational design, queries were more complex to express than in the object-oriented design, but more efficient to execute. It was concluded that the DR design should use standard relational tables while using objects only when required for specialized processing, such as processing of graphs or scans.

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)0.003
metaresearch head score (Gemma)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.329
GPT teacher head0.475
Teacher spread0.146 · 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

Quick stats

Citations9
Published2003
Admission routes1
Has abstractyes

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