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Record W3097819886 · doi:10.21852/sem.2020.3.06

DANE Mechanizm i obszary wsparcia rozwoju współpracy transgranicznej oraz ochrony dziedzictwa i krajobrazu kulturowego w ramach programu „Interreg Polska – Słowacja”

2020· article· en· W3097819886 on OpenAlexaff

Bibliographic record

VenueSeminare Poszukiwania naukowe · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsCanadian Heritage
Fundersnot available
KeywordsSlovakAccessionPolitical scienceGeographyRegional developmentRegional scienceEu countriesEuropean unionCultural heritageNatural heritageBusinessEconomic growthInternational tradeArchaeologyEconomics

Abstract

fetched live from OpenAlex

In order to support the development of Polish and Slovak border regions, after the accession of both countries to the EU, the “Interreg Poland – Slovakia” Program was implemented. One of the priorities of the Program is the protection and use of the common Polish-Slovak cultural and natural heritage for the development of cross-border cooperation. As part of Interreg since 2004, EU-Structural Funds have co-financed joint Polish-Slovak projects implemented in selected counties/poviat located in the following voivodeships/provinces: Śląskie, Małopolskie, Podkarpackie (on the Polish side) and Žilinskom kraji, Prešovskom kraji and Košickým kraji (on the Slovak side). The next editions of Interreg are becoming increasingly popular in Poland and Slovakia including its recognition by experts as well as the implementation of a cross-border effect.

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)0.002
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 score0.028
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0070.003
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.006

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 head0.051
GPT teacher head0.352
Teacher spread0.302 · 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
Published2020
Admission routes1
Has abstractyes

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