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Record W1772204473

An Efficient On-Line Algorithm for Edge-Ranking of Trees

2008· article· en· W1772204473 on OpenAlexaff
Abul Kashem, Md Ehsanul Haque

Bibliographic record

VenueAmericanae (AECID Library) · 2008
Typearticle
Languageen
FieldComputer Science
TopicGraph Labeling and Dimension Problems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRanking (information retrieval)Computer scienceCombinatoricsGraphEnhanced Data Rates for GSM EvolutionAlgorithmLearning to rankLine (geometry)Path (computing)Time complexityMathematicsArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

An edge-ranking of a graph G is a labeling of the edges of G with positive integers such that every path between two edges with the same label ° contains an edge with label ¸ > °. In the on-line edge-ranking model the edges e1; e2 : : : ; em arrive one at a time in any order, where m is the number of edges in the graph. Only the partial information in the induced subgraph G[fe1; e2; ... ; eig] is available when the algorithm must choose a rank for ei. In this paper, we present an on-line algorithm for ranking the edges of a tree in time O(n2), where n is the number of vertices in the tree.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.895
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.242
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

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