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Record W1485721381 · doi:10.3233/ao-2012-0111

Ontology for Big Systems: The Ontology Summit 2012 Communiqué

2012· article· en· W1485721381 on OpenAlexaff
Todd Schneider, Ali Hashemi, Mike Bennett, Mary Brady, Cory Casanave, Henson Graves, Michael Grüninger, Nicola Guarino, Anatoly Levenchuk, Ernie Lucier, Leo Obrst, Steven R. Ray, Ram D. Sriram, Amanda Vizedom, Matthew West, Trish Whetzel, Peter Yim

Bibliographic record

VenueApplied Ontology · 2012
Typearticle
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsUniversity of Toronto
FundersNational Institute of Standards and Technology
KeywordsComputer scienceOntologySummitUpper ontologyProcess ontologyOntology alignmentInformation retrievalData scienceWorld Wide WebSemantic WebEpistemology

Abstract

fetched live from OpenAlex

The Ontology Summit 2012 explored the current and potential uses of ontology, its methods and paradigms, in big systems and big data: How ontology can be used to design, develop, and operate such systems. The systems addressed were not just software

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.041
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0080.005
Scholarly communication0.0120.015
Open science0.0020.012
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0070.002

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 head0.049
GPT teacher head0.270
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations14
Published2012
Admission routes1
Has abstractyes

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