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Record W7028861741

Historical, semantic and structural aspects of marine terminology: A case study of Canadian variant of French

2018· other· ru· W7028861741 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Repository Saint Petersburg State University (Saint Petersburg State University) · 2018
Typeother
Languageru
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Set (abstract data type)Context (archaeology)Feature (linguistics)Semantics (computer science)
DOInot available

Abstract

Исследование посвящено изучению исторических, структурных и семантических вопросов морской терминологии на основе сравнения терминологических систем французского языка Франции и канадского варианта французского языка, а также изучению влияния возможных особенностей на процесс перевода текстов данной тематики. Представлен анализ развития специализированной лексики в области морского дела и навигации в контексте особых географических и исторических условий Канады. Дается определение понятий «термин» и «терминологическая система». В качестве основного метода исследования используется реверсивный метод, который позволяет установить уровень эквивалентности между терминами и выявить типичные ошибки при составлении двуязычных терминологических словарей.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: about_only · design weight: 3321.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: medium

Study of marine terminology in Canadian French; terminology and translation linguistics, not the research system.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

This linguistic study examines marine terminology and translation rather than research itself.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Linguistic/terminological comparison of French marine vocabulary; object is language and translation, not research itself.

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)0.006
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: Other · Consensus signal: none
Teacher disagreement score0.099
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.011
Science and technology studies0.0110.008
Scholarly communication0.0070.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.028
GPT teacher head0.248
Teacher spread0.220 · 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
GenreOther

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueResearch Repository Saint Petersburg State University (Saint Petersburg State University)French-language works237,207