MétaCan
Menu
Back to cohort
Record W4293248785 · doi:10.1145/3559736.3559739

Complexity column

2022· article· en· W4293248785 on OpenAlexaffabout
Andreĭ A. Bulatov

Bibliographic record

VenueACM SIGLOG News · 2022
Typearticle
Languageen
FieldComputer Science
TopicConstraint Satisfaction and Optimization
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsColumn (typography)Constraint satisfaction problemGeneralizationConstraint (computer-aided design)Computer scienceQuarter (Canadian coin)Theoretical computer scienceMathematicsArtificial intelligenceGeographyTelecommunications

Abstract

fetched live from OpenAlex

This quarter's Complexity column is devoted to the Promise Constraint Satisfaction Problem (PCSP). This framework was introduced relatively recently by Austrin, Guruswami and Håstad as a generalization of the Constraint Satisfaction Problem ( CSP ) that has received quite a bit of attention in the last three decades. Although the CSP captures many naturally occurring algorithmic problems and the CSP research has been very successful with the majority of research questions settled, there are still some important problems it does not capture. The PCSP was designed to fix that.

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)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.511
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0080.007
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.5110.343

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 head0.045
GPT teacher head0.260
Teacher spread0.216 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueACM SIGLOG NewsSame topicConstraint Satisfaction and OptimizationFrench-language works237,207