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A Description Logic of Change.

2006· article· en· W167512791 on OpenAlexaff
Alessandro Artale, Carsten Lutz, David Toman

Bibliographic record

VenueInternational Joint Conference on Artificial Intelligence · 2006
Typearticle
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsUndecidable problemComputer scienceDescription logicDynamic logic (digital electronics)Modal logicDecidabilitySatisfiabilityLinear temporal logicTemporal logicMultimodal logicEXPTIMEBoolean satisfiability problemModalTheoretical computer scienceArtificial intelligenceAlgorithmComputational complexity theory

Abstract

fetched live from OpenAlex

We combine the modal logic S5 with the description logic (DL) ALCQI. In this way, we obtain a multi-dimensional DL, S5ALCQI, whose purpose is reasoning about change. S5ALCQI is capable of expressing that concepts and roles change over time, but cannot discriminate between changes in the past and in the future. Our main technical result is that S5ALCQI concept satisfiability with respect to terminologies of general concepts inclusions (GCIs) is decidable and 2-ExpTime-hard. We also provide a scenario based on temporal conceptual models with timestamping constraints in which the logic can be used.

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)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.098
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0100.011
Open science0.0020.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0980.047

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 head0.322
GPT teacher head0.339
Teacher spread0.018 · 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 designTheoretical or conceptual
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

Citations12
Published2006
Admission routes1
Has abstractyes

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