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Record W7134019954

РОЛЬ КЛАСТЕРНИХ УТВОРЕНЬ У РОЗВИТКОВІ ПРОСТОРОВОЇ ЕКОНОМІКИ

2024· article· uk· W7134019954 on OpenAlexfundno aff
П.Т. Бубенко, В.В. Воліков

Bibliographic record

VenueA.N.Beketov KNUME Digital Repository (National University of Kharkiv) · 2024
Typearticle
Languageuk
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
FundersDalhousie UniversityEuropean Commission
KeywordsProcess (computing)Identification (biology)Product (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

Харківський національний університет міського господарства імені О.М.Бекетова, Україна 2 Дніпропетровський науково-дослідний інститут судових експертиз, Дніпро, Україна РОЛЬ КЛАСТЕРНИХ УТВОРЕНЬ У РОЗВИТКОВІ ПРОСТОРОВОЇ ЕКОНОМІКИ Стаття присвячена аналізу кластерних утворень як чинника підвищення конкурентоспроможності сучасних територіальних систем.Розглядаються різні підходи до дослідження сутності кластерів.Виділено загальні та специфічні риси кластерів, запропоновано авторське визначення поняття «кластер».Підсумовано, що завдяки синергетичним ефектам підвищується конкурентоспроможність кластера загалом та його окремих учасників, а також інноваційний рівень розвитку територіальної системи.

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)0.002
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 score0.027
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.014

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 head0.007
GPT teacher head0.178
Teacher spread0.171 · 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
Published2024
Admission routes1
Has abstractyes

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