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Record W2399228482

Context Derivation Sets and Context-Free Normal Forms.

2002· article· en· W2399228482 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDCFS · 2002
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsTerminal and nonterminal symbolsContext-free grammarSymbol (formal)Context-sensitive grammarTree-adjoining grammarMathematicsGrammarContext (archaeology)Mildly context-sensitive grammar formalismComputer scienceIndexed grammarRule-based machine translationNatural language processingLinguisticsGenerative grammarArtificial intelligencePhrase structure rulesProgramming language
DOInot available

Abstract

fetched live from OpenAlex

A set of transformations is presented that will convert an arbitrary context-tree grammar to six of the normal forms for which the right hand side of any production has at most two occurrences of nonterminal symbols. These transformations form the basis of a meta-normal form algorithm for context-free grammars. The algorithm takes as input an arbitrary context-free grammar and a target normal form, expressed as an extended two-symbol grammar form, and converts the grammar to that normal form. The number of nonterminals and productions in the output grammars of each of the base transformations is minimal.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.238
Teacher spread0.222 · 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