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Record W2266623466 · doi:10.4000/lapurdum.2393

Hizkeren arteko aldakortasun sintaktikoa aztertzeko metodologiaren nondik norakoak : BASYQUE aplikazioa

2012· article· eu· W2266623466 on OpenAlexaff
Larraitz Uria, Ricardo Etxepare

Bibliographic record

VenueLapurdum · 2012
Typearticle
Languageeu
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

Artikulu honetan BASYQUE aplikazioa sortzeko jarraitu den metodologia aurkezten da, metodologia horren inguruko hainbat gogoetarekin batera. Aplikazio hau Iparraldeko hizkeren baitako bariazio sintaktikoa biltzera mugatzen den arren, baliatzen diren metodologia eta bitartekoak erabilgarriak dira beste hizkera batzuen inguruan ere antzeko aplikazioak sortu eta bariazioaren inguruko azterbide berriak irekitzeko.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0100.008
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0210.005

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 head0.028
GPT teacher head0.287
Teacher spread0.259 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2012
Admission routes1
Has abstractyes

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