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Record W2203718738

Integration of Sequence of Computational Modules Dedicated to Text Analysis: A Combinatory Typed Approach

2013· article· en· W2203718738 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

VenueThe Florida AI Research Society · 2013
Typearticle
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsComputer scienceProgramming languageProcess (computing)Rule-based machine translationRepresentation (politics)Sequence (biology)Chain (unit)GrammarTheoretical computer scienceFormal languageArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

In informational terms, a module dedicated to process information always has specific inputs and outputs. It describes a particular process constrained by specific rules. A processing chain can be a serial combination and/or a parallel combination of such modules. Thus, in an architecture of language engineering, each processing chain becomes a particular instantiation of all possible paths. A processing chain is built from a choice of modules underlying tasks that an engineer wants to apply to the text. In our paper we will present our theoretical model of logical representation of the processing chains, based on combinatory logic and a formal approach based on categorial grammars and applicative grammar, along with many cases of modules configurations.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.675
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.065
GPT teacher head0.346
Teacher spread0.281 · 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