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Record W2406034771

On the Synchronized Derivation Depth of Context-Free Grammars.

2008· article· en· W2406034771 on OpenAlexaff
Franziska Biegler, Kai Salomaa

Bibliographic record

VenueDCFS · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Biological Computing
Canadian institutionsQueen's UniversityWestern University
Fundersnot available
KeywordsTree-adjoining grammarIndexed grammarRule-based machine translationL-attributed grammarContext-free grammarMeasure (data warehouse)Embedded pushdown automatonContext (archaeology)Context-sensitive grammarMathematicsSynchronization (alternating current)Tree (set theory)Deterministic context-free grammarComputer scienceCombinatoricsArtificial intelligenceGeographyTopology (electrical circuits)
DOInot available

Abstract

fetched live from OpenAlex

We consider depth of derivations as a complexity measure for synchronized and ordinary context-free grammars. This measure differs from the earlier considered synchronization depth in that it counts the depth of the entire derivation tree. We consider (non-)existence of trade-offs when using synchronized grammars as opposed to non-synchronized grammars and establish lower bounds for certain classes of linear context-free languages.

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)0.004
metaresearch head score (Gemma)0.033
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 score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.005
Scholarly communication0.0030.014
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.023
GPT teacher head0.229
Teacher spread0.206 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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