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Record W2170426700 · doi:10.5539/ijel.v5n5p164

Intonative Variety of Simple Declarative Sentences in the English Language

2015· article· en· W2170426700 on OpenAlexvenueno aff
Allahverdiyeva Feride Mahammad

Bibliographic record

VenueInternational Journal of English Linguistics · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiscourse Analysis and Cultural Communication
Canadian institutionsnot available
Fundersnot available
KeywordsIntonation (linguistics)Variety (cybernetics)SentenceLinguisticsSyntaxComputer sciencePhraseSituational ethicsNatural language processingArtificial intelligencePsychology

Abstract

fetched live from OpenAlex

The issue of investigation of structural-syntactic and intonation types and kinds of different sentences in the language, began to be broaden since the third decade of the XX century. The investigation of sentence intonation in the initial stage was more linked with teaching of the languages. In the later period alongside the linguists, psychologists, physics, and specialists of other branches of science also were engaged in the study of speech intonation. Up to the last years, in the carried out investigations, the main attention was paid to the formal investigation of intonation structure of communicative types of sentences. That’s why only the structural-semantic analysis of communicative and derivational types of sentences was not satisfactory enough to discover their semantic contents as a whole. But in the modern stage, study of syntax of sentence and its semantics in the plan of intonation variety, proved that the investigation of this problem is more actual than ever today. Thus, comparative study of sentence belonging to each communicative type, including the study of phono-semantic variety of simple types of declarative sentences in the English language which we carry out in a certain contextual-situational phrase, with intonative variety, bears a special importance in the modern stage. A sentence in a certain situation is used for a special purpose and receives an adequate form of intonation. The same sentence in different contexts is never expressed with the same intonation counters. It is in a certain degree subjected to different variations.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.379
Teacher spread0.334 · 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 designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicDiscourse Analysis and Cultural CommunicationFrench-language works237,207