MétaCan
Menu
Back to cohort
Record W1739817710 · doi:10.3233/ifs-2008-00377

Fusion devices and changes of belief

2008· article· en· W1739817710 on OpenAlexaff
Eugene Rovenţa, Tiberiu Spircu

Bibliographic record

VenueJournal of Intelligent & Fuzzy Systems · 2008
Typearticle
Languageen
FieldComputer Science
TopicLogic, Reasoning, and Knowledge
Canadian institutionsYork University
Fundersnot available
KeywordsState (computer science)FusionSensor fusionSentenceComputer scienceArtificial intelligenceBelief revisionIntelligent agentDempster–Shafer theoryAlgorithmLinguistics

Abstract

fetched live from OpenAlex

After receiving a piece of evidence Π, intelligent agents adapt their belief state. Knowing the belief state of several sensor agents, a fusion agent forms its own belief state. A belief state (old or new) is characterized by numbers μ(A) attached to subsets A of the universe of worlds. (Usually μ(A) is interpreted as that part of the belief of an agent in the sentence "the actual world belongs to A" and not in any sentence "the actual world belongs to a strict subset of A".) In this paper we study how fusion agents treat changes of belief state of sensors. Two kinds of fusion are considered: the averaging by convex combination, and Dempster type conjunctive rules of combination. We establish that there is no coherent treatment, at the fusion agents' level, that is compatible with both kinds of fusion. To deal with better detection, a mixed structure involving intermediate supervision agents is proposed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.360

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)0.0000.000

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 head0.032
GPT teacher head0.247
Teacher spread0.215 · 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.

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

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
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Intelligent & Fuzzy SystemsSame topicLogic, Reasoning, and KnowledgeFrench-language works237,207