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Record W4394987214 · doi:10.4204/eptcs.402.10

CHC-COMP 2023: Competition Report

2024· article· en· W4394987214 on OpenAlexaff
Emanuele De Angelis, Hari Govind V K

Bibliographic record

VenueElectronic Proceedings in Theoretical Computer Science · 2024
Typearticle
Languageen
FieldComputer Science
TopicFormal Methods in Verification
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCompetition (biology)French hornClass (philosophy)Computer scienceOperations researchEngineeringSociologyArtificial intelligence

Abstract

fetched live from OpenAlex

CHC-COMP 2023 is the sixth edition of the Competition of Solvers for Constrained Horn Clauses. The competition was run in April 2023 and the results were presented at the 10th Workshop on Horn Clauses for Verification and Synthesis held in Paris, France, on April 23, 2023. This edition featured seven solvers (six competing and one hors concours) and six tracks, each of which dealing with a class of clauses. This report describes the organization of CHC-COMP 2023 and presents its results.

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)0.025
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.161
Threshold uncertainty score0.537

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.027
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.005
Science and technology studies0.0040.001
Scholarly communication0.0120.006
Open science0.0060.005
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.1610.127

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 head0.007
GPT teacher head0.277
Teacher spread0.269 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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Same venueElectronic Proceedings in Theoretical Computer ScienceSame topicFormal Methods in VerificationFrench-language works237,207