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Record W7135967858

Morphological and syntactic charakteristics of the expressions half and quarter

2019· dissertation· cs· W7135967858 on OpenAlexaboutno aff
Anna Josefína Nováková

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2019
Typedissertation
Languagecs
FieldSocial Sciences
TopicLiterature, Language, and Rhetoric Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNumeral systemQuarter (Canadian coin)CzechNounPredicate (mathematical logic)Noun phraseSentenceGenitive case
DOInot available

Abstract

fetched live from OpenAlex

1 Abstract This bachelor's thesis aims to provide a morphological and syntactical analysis of Czech expressions půl "a half"and čtvrt "a quarter". The first part deals with the description and characteristics of numerals in specialized literature, with focus on the explored expressions, and it then proceeds to define the research questions (e. g. to what extent are the forms frozen; forms of the noun denoting the counted object (JPP) etc.), which are then explored in the practical part, using corpus analysis. The data used in the analysis are taken from the SYN2015 corpus. The analysed sample contains 1 000 of the čtvrt lemmas and the same number of the půl lemmas. The analysis shows that the expressions resemble one another in several aspects: e. g. the low number of non-frozen forms (e. g. do půli stehna "halfway up/down the thigh"); JPP have mostly genitive form in direct cases (e. g. půl dne "a half of a day", čtvrt měsíce "a quarter of a month"); and in indirect cases, the form of JPP is mostly dependent on higher sentence structure (e. g. s půl dnem "with a half of a day", o čtvrt roce "about a quarter of a year"), and they have the same predicate agreement like the numerals of the pět "five" type (e. g. půl roku uplynulo "half a year passed", čtvrt koláče zbylo "a quarter of the pie is left"). But...

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)0.004
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.261
Teacher spread0.252 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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