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Record W7049108765

The nonword repetition task as a procedure for assessing phonological development at the preschool age : the possibility of specific language impairment discrimination in the Serbian language

2017· article· sh· W7049108765 on OpenAlexaboutno aff

Bibliographic record

VenueFaculty of Philosophy (University of Belgrade) · 2017
Typearticle
Languagesh
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsNoise (video)Ethnic groupStatistical analysisNova scotia
DOInot available

Abstract

fetched live from OpenAlex

Specifični jezički poremećaj (SJP) je heterogeni razvojni jezički poremećaj koji podrazumeva značajan deficit u jezičkoj sposobnosti (sa posebnim slabostima u domenu fonologije i morfo-sintakse) koji se ne može pripisati oštećenju sluha, niskoj neverbalnoj inteligenciji, neurološkim oštećenjima, emocionalnoj i socijalnoj deprivaciji i drugim poznatim faktorima. Zadatak ponavljanja pseudoreči koji se sastoji u izlaganju i trenutnom ponavljanju izmišljenih reči (pseudoreči) i ispituje sposobnost fonološke reprodukcije je, prema nalazima istraživanja u drugim jezicima, obećavajući psiholingvistički marker za SJP iz razloga što deca sa SJP konzistentno imaju slabiji uspeh na ovom zadatku u odnosu na svoje vršnjake tipičnog razvoja (TR). Cilj istraživanja prikazanog u ovoj disertaciji je da se primenom zadatka ponavljanja pseudoreči, konstruisanih u skladu sa karakteristikama srpskog jezika, ispita sposobnost fonološke reprodukcije TR i SJP dece predškolskog i ranog školskog uzrasta koja usvajaju srpski jezik i da se utvrde razvojno diskriminativni i parametri diskriminativni za SJP koji će poslužiti za konstrukciju testa. Ovakav test bi omogućio procenu fonološkog razvoja kod dece koja usvajaju srpski jezik i, uz dodatne procene stručnjaka u kliničkoj praksi, omogućio diskriminaciju SJP i, potencijalno, drugih govorno-jezičkih teškoća kod dece...

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.300
Teacher spread0.268 · 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 teacher head, not a consensus.

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
Published2017
Admission routes1
Has abstractyes

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