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Record W2960042986 · doi:10.4000/geolinguistique.570

Torres, castelos e castros no mapa linguístico de Portugal Continental

2016· article· es· W2960042986 on OpenAlexaff
Luís Fernando Pinto Salema

Bibliographic record

VenueGéolinguistique · 2016
Typearticle
Languagees
FieldArts and Humanities
TopicMedieval Iberian Studies
Canadian institutionsContinental (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhysicsPhilosophy

Abstract

fetched live from OpenAlex

O artigo lança um olhar sobre os topónimos de Portugal Continental, assente nas palavras «Castelo», «Castro» e «Torre». Analisaram-se os topónimos do ponto de vista morfológico e sintático. A análise permitiu identificar três grandes grupos, tendo em conta as estruturas mórficas ocorrentes: 1) topónimos com o nome simples; 2) topónimos com variações em grau, género e número ou com sufixos derivacionais; 3) compostos sintagmáticos, com ou sem elementos conetivos, estrutura que se revelou mais produtiva e com maior variação nos processos compositivos. Nestes compostos, a definição do núcleo do sintagma toponímico pode ser problemática, parecendo assentar em critérios pragmáticos e culturais.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.020
GPT teacher head0.259
Teacher spread0.239 · 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 designNot applicable
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

Citations1
Published2016
Admission routes1
Has abstractyes

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