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Record W2148375944 · doi:10.1109/cwit.2007.375705

On the Interpretation of Survey Propagation

2007· article· en· W2148375944 on OpenAlexaff
Ronghui Tu, Yongyi Mao, Jiying Zhao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicConstraint Satisfaction and Optimization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBelief propagationProbabilistic logicComputer scienceConstraint (computer-aided design)Decoupling (probability)Token passingSecurity tokenMessage passingLocal consistencyInterpretation (philosophy)Reduction (mathematics)Propagation of uncertaintyConstraint satisfaction problemConstraint satisfactionTheoretical computer scienceArtificial intelligenceAlgorithmMathematicsDistributed computingComputer securityEngineeringProgramming language

Abstract

fetched live from OpenAlex

In this paper, we unify survey propagation (SP) for constraint-satisfaction problems as "probabilistic token passing" algorithms. We show that the reduction of SP from belief propagation (BP) for general problems requires a modification of the BP message-passing rule, namely, introducing what we call a state-decoupling operation on the BP messages. This raises a question mark on the recent "folk belief" that SP is BP.

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)0.007
metaresearch head score (Gemma)0.027
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.007
Scholarly communication0.0050.013
Open science0.0030.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.021
GPT teacher head0.252
Teacher spread0.231 · 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
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

Citations2
Published2007
Admission routes1
Has abstractyes

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